Jobs — Data Scientists

AI and Data Science Engineer III

Deloitte · Seattle, WA

Mid-level Doctorate

2026-06-05

WA 2026-06-05

Requirements

Bachelor's degree in a STEM field (e.g., Computer Science, Engineering, Statistics, Data Science)
4+ years of experience in data science, analytics, or a related field - with direct experience in client-facing or consulting environments.
4+ years of demonstrated proficiency in SQL for data extraction, transformation, and analysis across relational databases.
4+ years of demonstrated proficiency in Python or R for statistical modeling and data wrangling.
4+ years of hands-on experience with data visualization tools such as Tableau, Power BI, or equivalent platforms.
4+ years of building analytics solutions end-to-end: from data ingestion and modeling to visualization and stakeholder presentation.
Ability to travel 0-25%, on average, based on client and project needs.
Limited immigration sponsorship may be available

Preferred

Advanced degree (MS/PhD) and/or relevant certifications (data science and AI/ML).
Experience working with workforce, HR, or human capital data (e.g., headcount, attrition, compensation, organizational network analysis).
AI fluency and familiarity with machine learning concepts, large language model applications, or AI-augmented analytics workflows.
Economics background or acumen, with the ability to apply labor market economics principles to workforce problems.
Experience in analytics product development - building repeatable tools, models, or platforms rather than one-off deliverables.
Proficiency in Python or R for statistical modeling and data wrangling.
Strong communication skills with the ability to convey complex analytical insights to diverse audiences.
The wage range for this role takes into account the wide range of factors that are considered in making compensation decisions including but not limited to skill sets; experience and training; licensure and certifications; and other business and organizational needs. The disclosed range estimate has not been adjusted for the applicable geographic differential associated with the location at which the position may be filled. At Deloitte, it is not typical for an individual to be hired at or near the top of the range for their role and compensation decisions are dependent on the facts and circumstances of each case. A reasonable estimate of the current range is $122,000 to $240,500.
You may also be eligible to participate in a discretionary annual incentive program, subject to the rules governing the program, whereby an award, if any, depends on various factors, including, without limitation, individual and organizational performance.

Responsibilities

Lead the design, development, and delivery of analytics solutions that address complex workforce and human capital challenges for clients across industries.
Build and maintain scalable data pipelines, dashboards, and reporting frameworks using SQL and Tableau (or equivalent visualization platforms).
Translate ambiguous business problems into structured analytical approaches, communicating findings and recommendations clearly to both technical and non-technical stakeholders.
Collaborate across service lines to embed AI-enabled capabilities and emerging data methodologies into client solutions.
Support business development efforts including proposals, client presentations, and thought leadership content.
Design and deliver intuitive, executive-ready reports and dashboards that make complex workforce data accessible and actionable.
Apply economic and statistical reasoning to interpret workforce trends, model scenarios, and support evidence-based decision-making.
A successful candidate would possess these skills:
Ability to work independently and collaborate as part of a team
Effective written and verbal communication skills
Meticulous attention to detail and quality of work product
Ability to build and sustain professional relationships
Ability to lead projects or workstreams
Ability to manage and prioritize multiple tasks in a fast-paced and dynamic environment
Strong interpersonal skills and professional demeano
Ability to meet deadlines
Ability to provide clear guidance to others
HC Forward is a dedicated innovation partner accelerating the future of Human Capital by building market-aligned products, platforms, and services that apply AI, data, and engineering to modernize HR experiences and outcomes.

View full posting on CareerOneStop → ID: 046cdce469aa

Data Scientist Engineer - SFL Scientific

Deloitte · Seattle, WA

Mid-level Doctorate

2026-06-05

WA 2026-06-05

Requirements

Master's or Ph.D. in a relevant STEM field (Data Science, Computer Science, Engineering, Physics, Mathematics, etc.)
2+ years of experience in AI/ML algorithm development using core data science languages and frameworks (Python, PyTorch, etc.) and data analysis (NLP, time-series analysis, computer vision)
2+ years of experience and a proven track record applying traditional ML and deep learning techniques (CNNs, RNNs, GANs) across real-world projects, including model tuning and performance validation in production environments
2+ years of experience deploying and optimizing ML models using tools like Kubernetes, Docker, TensorRT/Triton, RAPIDs, Kubeflow, and MLflow
2+ years of experience in leveraging cloud environments (AWS, Azure, or GCP) to deploy AI/ML workloads
Live within commuting distance to one of Deloitte's consulting offices
Ability to travel 10%, on average, based on the work you do and the clients and industries/sectors you serve
Limited immigration sponsorship may be available

Preferred

2+ years of experience working in a client-facing, consulting environment
1+ years of experience leading project/client engagement teams in the execution of complex AI data science solutions
1+ year of experience with LLM/GenAI use cases and developing RAG solutions, agent-based tools and services, and GenAI frameworks (i.e., LangChain, LangGraph, MCP, etc.)
1+ year of experience with AWS Sagemaker or AWS ML Studio
The wage range for this role takes into account the wide range of factors that are considered in making compensation decisions including but not limited to skill sets; experience and training; licensure and certifications; and other business and organizational needs. The disclosed range estimate has not been adjusted for the applicable geographic differential associated with the location at which the position may be filled. At Deloitte, it is not typical for an individual to be hired at or near the top of the range for their role and compensation decisions are dependent on the facts and circumstances of each case. A reasonable estimate of the current range is $95,600 to $188,400.
You may also be eligible to participate in a discretionary annual incentive program, subject to the rules governing the program, whereby an award, if any, depends on various factors, including, without limitation, individual and organizational performance.

View full posting on CareerOneStop → ID: ce298ebdb793

Data Scientist, Finance

Meta · Bellevue, WA

Mid-level Doctorate

2026-06-05

WA 2026-06-05

Requirements

Bachelor's degree in a directly related field, or equivalent practical experience
A minimum of 12 years of work experience in analytics (minimum of 8 years with a Ph.D.)
Experience with data querying languages (e.g., SQL), scripting languages (e.g., Python), and/or statistical/mathematical software (e.g., R)

Preferred

Demonstrated ability to integrate AI tools to optimize/redesign workflows and drive measurable impact (e.g., efficiency gains, quality improvements)
Experience adhering to and implementing responsible, ethical AI practices (e.g., risk assessment, bias mitigation, quality and accuracy reviews)
Demonstrated ongoing AI skill development (e.g., prompt/context engineering, agent orchestration) and staying current with emerging AI technologies
Master's or Ph.D. degree in a quantitative field
Experience working in a data science role at a hyperscaler / public cloud and / or a large customer of a public cloud company
Experience partnering cross-functionally with a wide range of teams, dealing with ambiguous and presenting technical content in an easy to understand manner to technical and non-technical teams
Knowledge of business outcomes and technology investments and experience connecting them to practical models for decision making

Responsibilities

Meta is seeking a Data Scientist to join the data science team in the Finance organization that partners very closely with Product, AI, Infrastructure, Finance and other Data Science teams across the company. These teams are building some of the most cutting edge and transformative AI products in the world that are being rolled out to Meta's 3 Billion+ users. Building these products and features requires tens of billions of dollars of capital each year over a sustained period of time. Managing and optimizing the deployment of this vast capital and the allocation of these resources requires a team that has technical expertise in AI and Infrastructure along with a solid understanding of data science, finance and operations. This position will use data and analysis to identify and solve product development's biggest challenges and will require an understanding of how AI and Infrastructure are built, operated and used to serve users. This role will help establish the ROI and company-wide prioritization of such investments and work on solving some of the most important technological problems of our times and also ensure that the company makes efficient investments. As an individual contributor, you will influence product strategy and investment decisions with data, be focused on impact, and collaborate with other teams. By joining Meta, you will become part of a high-performing analytics community dedicated to skill development and career growth in analytics and beyond.
Work with large and complex data sets to solve a wide array of problems using different analytical and statistical approaches
Apply technical expertise with quantitative analysis, experimentation, data mining, and the presentation of data to build and maintain end-to-end models for long range planning and strategic decisions
Build models to compute and explain Infrastructure OPEX and CAPEX costs at the company, product and resource levels
Leverage understanding of AI and Infrastructure to develop point-of-view on ROI of investments in Infrastructure and allocation of Infrastructure resources to various products and software platforms
Identify and measure success infrastructure investments through goal setting, forecasting, and monitoring of key metrics to understand trends
Help define resource allocation policies that are reasonable and actionable from a technical, operational and financial perspective
Work with product, engineering and data science teams to do technical, operational and business impact assessments of re-allocation of resources based on changing business needs, competitive landscape and product roadmaps
Maintain lineage of decisions around Infrastructure investments and assumptions under which those decisions were made to drive accountability for outcomes across the company
Define, understand, and test opportunities and levers to improve the our models, and drive roadmaps through your insights and recommendations
Partner with Product, Engineering, and cross-functional teams to inform, influence, support, and execute product strategy and investment decisions

View full posting on CareerOneStop → ID: 5cac8678fb28

Data Scientist, Fleet Planning , Global Fleet Products

Amazon · Bellevue, WA

Mid-level Master's

2026-06-05

WA 2026-06-05

Requirements

5+ years of data querying languages (e.g. SQL), scripting languages (e.g. Python) or statistical/mathematical software (e.g. R, SAS, Matlab, etc.) experience
Master's degree in operations research, applied mathematics, theoretical computer science, or equivalent, or a Associate's degree or above and experience investigating the feasibility of applying scientific principles and concepts to business problems and products

Preferred

2+ years of data visualization using AWS QuickSight, Tableau, R Shiny, etc. experience
Experience managing data pipelines
Experience as a leader and mentor on a data science team

Responsibilities

Build models and automation for planners for generating vehicle allocation plans
Partner with program teams to test and measure success of implemented model
Lead reviews with senior leadership, deep dive model outputs and explain implications of model recommendations.

View full posting on CareerOneStop → ID: b1b087e9e938

Machine Learning Engineer - Visual Intelligence

Apple · Seattle, WA

Mid-level

2026-06-05

WA 2026-06-05

Requirements

0-10 years of professional experience writing software
Experience working on any of the following: computer vision, real-time perception, digital signal processing, camera/sensor pipelines, sensor fusion, ISPs, robotics, or related technologies at the intersection of sensor hardware, software, and machine learning

Preferred

Experience using Swift, Xcode and Apple's developer APIs a plus
A learning mentality and a willingness to try things that may fail. You should be able to learn from both success and failures.
Ability to communicate effectively with both technical and non-technical teams
Ability to thrive in a fast-paced, highly collaborative team environment
A background in Computer Science, Computer Engineering, Electrical Engineering, or related plus experience shipping software is ideal. Experience working with computer vision, machine learning, digital signal processing, robotics, or related are a plus. If that's not your background, but you can show a strong track record of software development, curiosity, making, and learning, we'd love to talk to you.

Responsibilities

Visual Intelligence is a new feature that enables users to learn about the objects and places around them. We are a new and growing team building the future of user experiences at the intersection of computer vision, machine learning and Apple intelligence. This is an exciting time to join and have impact at the core of Apple's future roadmap for Apple Intelligence. We are especially looking for people who love to collaborate across disciplines and teams, and are motivated and inspired by the potential to help shape the future of system experiences across the entire Apple ecosystem.
We are looking for a software engineer to work on building the next generation of features for Visual Intelligence, including CV/ML, sensor fusion, simulation/evaluation pipelines, APIs, and core backend software components. Our work is primarily in Swift, so prior experience is highly preferred. If you are an outstanding software engineer with no Swift experience, we'd still love to hear from you.

View full posting on CareerOneStop → ID: 5eaa5efe4bd4

Machine Learning Research Engineer , Text Generation, Input Experience

Apple · Seattle, WA

Mid-level Master's

2026-06-05

WA 2026-06-05

Requirements

Strong machine learning fundamentals
Knowledge of ML techniques such as implementing basic optimizers, applying parameter tuning in model training and evaluation, and reproducing research experiments
Strong programming and communication skills
Ph. D. in CS/EE/Physics/Statistics/etc. (or Masters with 4 years of proven experience)

Preferred

Familiar with model compression algorithms including quantization, pruning, distillations, and experience optimizing large diffusion models or language models
Experience with hardware architecture, software & hardware co-design
Experience with deploying large ML models in real world products
Actively programming with high-quality codes across complex and large repositories
Familiar with common NLP algorithms and applications, including tokenization, language modeling, text decoding, text classifier etc
Experience of multi-modal modeling, presenting plans, progress, and results or demos regularly and concisely

Responsibilities

Apple is where individual imaginations gather together, committing to the values that lead to great work. Every new product we build or service we create, what we deliver is the result of us making each other's ideas stronger. It's the diversity of our people and their thinking that inspires the innovation that runs through everything we do. When we bring everybody in, we can do the best work of our lives. Here, you'll do more than join something - you'll add something. Text generation is a key enabler for accelerated text input and intelligent interaction on Apple platforms.
Our team is working on redefining user interaction with generative models for text generation. If you want to be part of an ambitious, organized and collaborative team that ships user experiences with pioneering ML, partnered with the best UI designs, come join the Input Experience NLP team. Our work has been highlighted in multiple WWDC keynotes including Intelligent Input in 2023, Writing Tools and Smart Reply in 2024!
We exemplify Apple's outstanding integration of hardware and software to create seamless input experiences. You will have the opportunity to go from building offline pioneering NLP models to optimization of the models for different hardware backends and user interfaces that make the experience magical. Our vision always includes a deep dedication to strengthening Apple's privacy policy by achieving all of the above on device with powerful Machine Learning.
As a key pillar of Apple Intelligence, input experience will be the main area where you bring impact to billions of users with your Machine Learning expertise, engineering passion, and programming skills. You will work with a hard-working and dedicated set of outstanding ML and software engineers on a wide range of most advanced text generation technologies such as context-augmented text rewriting, safety-controlled text composition, free-form text transformation, personalized smart interactions, etc.
Our team has been working in this area for years and own the NLP and ML text input stack for the keyboard input that includes auto correction, predictive typing on all Apple platforms. We also work on full stack ML applied to NLP and expose these key technologies across Apple on device and also to third party applications through the Natural-Language framework. If you want to amplify your strong Machine Learning and NLP skills into user experiences that will reach every person around you, this is the perfect opportunity!

View full posting on CareerOneStop → ID: c6cfd50d8ceb

Software Engineer in Natural Language Processing (NLP) and Machine Learning (ML)

Apple · Seattle, WA

Mid-level

2026-06-05

WA 2026-06-05

View full posting on CareerOneStop → ID: 3e444df3356a

AI and Data Science Engineer III

Deloitte · Portland, OR

Mid-level

2026-06-05

WA 2026-06-05

View full posting on CareerOneStop → ID: c95ecf1bfce8

Data Scientist Engineer - SFL Scientific

Deloitte · Portland, OR

Mid-level

2026-06-05

WA 2026-06-05

View full posting on CareerOneStop → ID: 1178106ae846

AI and Data Science Engineer II

Deloitte · Seattle, WA

Mid-level Master's

2026-06-04

WA 2026-06-04

Requirements

Bachelor's degree in engineering, mathematics, physics, machine learning, statistics, computer science, or another quantitative field
2+ years of industry experience outside of academia applying data science or machine learning methods
Experience translating business goals into machine learning use cases and model design
Experience performing exploratory data analysis and developing predictive models
Ability to travel 30%, on average, based on the work you do and the clients and industries/sectors you serve.
Must be legally authorized to work in the United States without the need for employer sponsorship, now or at any time in the future.

Preferred

Master's degree in engineering, mathematics, physics, machine learning, statistics, computer science, or another quantitative field
Experience manipulating large marketing data sets and performing extract, transform, and load activities
Experience with boosted trees, logistic regression, classification techniques, unsupervised models, large language models, or experimental design
Experience with data sets generated in advertising technology or marketing technology environments
Experience presenting complex data insights to non-technical audiences
Experience with deep learning architectures or reinforcement learning
The wage range for this role takes into account the wide range of factors that are considered in making compensation decisions including but not limited to skill sets; experience and training; licensure and certifications; and other business and organizational needs. The disclosed range estimate has not been adjusted for the applicable geographic differential associated with the location at which the position may be filled. At Deloitte, it is not typical for an individual to be hired at or near the top of the range for their role and compensation decisions are dependent on the facts and circumstances of each case. A reasonable estimate of the current range is $86,700 - $170,900.
You may also be eligible to participate in a discretionary annual incentive program, subject to the rules governing the program, whereby an award, if any, depends on various factors, including, without limitation, individual and organizational performance.

View full posting on CareerOneStop → ID: c205110ea9aa

AIML - ML Engineer, Responsible AI

Apple · Seattle, WA

Mid-level Doctorate

2026-06-04

WA 2026-06-04

Requirements

Strong engineering skills and experience in writing production-quality code in Python, Swift or other programming languages
Background in generative models, natural language processing, LLMs, or diffusion models
Experience with failure analysis, quality engineering, or robustness analysis for AI/ML based features
Experience working with crowd-based annotations and human evaluations
Experience working on explainability and interpretation of AI/ML models
Work with highly-sensitive content with exposure to offensive and controversial content

Preferred

BS, MS or PhD in Computer Science, Machine Learning, or related fields or an equivalent qualification acquired through other avenues
Proven track record of contributing to diverse teams in a collaborative environment

Responsibilities

Would you like to play a part in building the next generation of generative AI applications at Apple? We're looking for scientists and engineers to work on ambitious projects that will impact the future of Apple, our products, and the broader world.
In this role, you'll have the opportunity to tackle innovative problems in machine learning, particularly focused on generative AI. As a member of the Apple HCMI group, you will be working on Apple's generative models that will power a wide array of new features. Our team is currently working on large generative models for vision and language, with particular interest on safety, robustness, and uncertainty in models.
Develop models, tools, metrics, and datasets for assessing and evaluating the safety of generative models over the model deployment lifecycle
Develop methods, models, and tools to interpret and explain failures in language and diffusion models
Build and maintain human annotation and red teaming pipelines to assess quality and risk of various Apple products
Prototype, implement, and evaluate new ML models and algorithms for red teaming LLMs

View full posting on CareerOneStop → ID: 147f72c89925

Data Scientist - Pricing

Microsoft Corporation · Redmond, WA

Mid-level Doctorate

2026-06-04

WA 2026-06-04

Requirements

Doctorate in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field
OR Master's Degree in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field AND 1+ year(s) data-science experience (e.g., managing structured and unstructured data, applying statistical techniques and reporting results) or consulting experience
OR Bachelor's Degree in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field AND 2+ years data-science experience (e.g., managing structured and unstructured data, applying statistical techniques and reporting results)
OR equivalent experience.

Preferred

Doctorate in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field AND 1+ year(s) data-science experience (e.g., managing structured and unstructured data, applying statistical techniques and reporting results)
OR Master's Degree in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field AND 3+ years data-science experience (e.g., managing structured and unstructured data, applying statistical techniques and reporting results)
OR Bachelor's Degree in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field AND 5+ years data-science experience (e.g., managing structured and unstructured data, applying statistical techniques and reporting results)
Experience in Python, R, or similar languages
Experience with Azure Machine Learning (ML) or equivalent cloud-based ML platforms.
Experience working with large-scale data and distributed systems.
Experience with yield or revenue management, pricing optimization, or cloud resource allocation.
Data Science IC3 - The typical base pay range for this role across the U.S. is USD $102,100.00 - $202,200.00 per year. There is a different range applicable to specific work locations, within the San Francisco Bay area and New York City metropolitan area, and the base pay range for this role in those locations is USD $133,800.00 - $219,200.00 per year.
Certain roles may be eligible for benefits and other compensation. Find additional benefits and pay information here:

Responsibilities

Data Analysis & Modeling: Analyze large-scale datasets to identify patterns, trends, and opportunities for improving yield and efficiency.
Yield Optimization: Develop machine learning models to optimize resource allocation and pricing strategies.
Cross-Functional Collaboration: Partner with business planning, engineering, product management, and finance teams to align yield strategies with business objectives.
Experimentation & A/B Testing: Design and execute experiments to validate optimization hypotheses. Build causal inference models (e.g., difference-in-difference, synthetic control) to measure the impact of business decisions.
Data Visualization : Develop dashboards and other visuals to monitor key business trends, identify new opportunities, and translate findings to actionable insights.
Thought Leadership : Stay current with industry trends in AI, cloud economics, and optimization techniques; share insights and best practices internally.
Other : Embody our Culture (https://www.microsoft.com/en-us/about/corporate-values) and Values (https://careers.microsoft.com/us/en/culture)

View full posting on CareerOneStop → ID: 998bf2a4b542

Machine Learning Engineer - News, Books, and Stocks Team

Apple · Seattle, WA

Mid-level Doctorate

2026-06-04

WA 2026-06-04

Requirements

MS in Machine Learning, Computer Science, or related field. Alternatively, equivalent industry experience to an MS degree is acceptable.
At least 2 years of experience shipping machine learning models in products.
Strong programming skills in Python, Java, or a related language, and one of the deep learning toolkits such as PyTorch, TensorFlow, or similar.
Ability to communicate effectively and collaborate with partner teams.
Commitment to encouraging an open and inclusive work environment.

Preferred

Ph.D. in Machine Learning, Computer Science, or related field.
At least 5 years of experience shipping machine learning models in products.
Experience with recommender systems.
Experience with text-centric AI/ML (LLMs, document classification, search, etc.)
Experience delivering high quality software at scale.
Experience designing user-facing machine learning features with interdisciplinary partners.

Responsibilities

In a time where the news and book media landscapes are changing by the day, Apple News and Apple Books stand as champions of quality content, expert curation, user privacy, and the judicious use of machine learning. Our lively and brilliant team consists of client and machine learning engineers who embody Apple's values. We inspire, teach, and otherwise enable each other to do the best work of our careers. Our team's outstanding retention rate speaks to our strong culture of respect for our teammates as both engineers and people. Would you like to work on such a team, solving hard problems in machine learning? Terrific! Please join us for the next generation of these apps!
Our team is seeking a high-energy and self-driven machine learning engineer who will play a central role in the delivery of scalable services. The team uses machine learning to tackle difficult and complicated problems in the news, books, and stocks domains, including text extraction, named entity recognition, duplicate detection, search, ranking, and much more! As a member of our dynamic group, you'll have the rare and rewarding opportunity to craft upcoming products that will delight and encourage millions of Apple's customers every day!

View full posting on CareerOneStop → ID: c912119310d9

Machine Learning Engineer

Robinhood Markets, Inc. · Bellevue, WA

Mid-level

2026-06-04

WA 2026-06-04

View full posting on CareerOneStop → ID: 8b5f95620c97

Machine Learning Engineer

FlightSafety International Inc · Seattle, WA

Mid-level

2026-06-03

WA 2026-06-03

Preferred

Experience with distributed task queues or stateful workflow engines for managing complex, multi-step AI processes
Experience with frameworks designed for horizontal scaling of compute-intensive ML workloads
Experience designing "agent-loop" architectures that involve tool-use, self-correction, and multi-step reasoning
Familiarity with vector storage systems and high-throughput data processing pipelines
Wage Transparency
Pay for this position is based on a number of factors includi

Responsibilities

As a Machine Learning Engineer on the AI Platform team, you will design and build the foundational infrastructure that powers Docusign's next generation of intelligent systems. You will bridge the gap between core AI research and production-grade engineering, developing scalable platforms for autonomous agents, advanced retrieval systems, and automated model optimization.
This position is an individual contributor role reporting to the
Director, Machine Learning Engineering
*Responsibility
Build and maintain high-performance distributed systems to support large-scale model inference and data processing
Design frameworks for multi-agent systems, focusing on state management, reliability, and long-running autonomous workflows
Architect sophisticated Retrieval-Augmented Generation (RAG) pipelines and advanced context management strategies to improve model accuracy and relevance
Develop platform-level tools for automated prompt engineering, evaluation, and optimization to accelerate the AI development lifecycle
Implement robust ML pipelines, focusing on observability, versioning, and the seamless deployment of generative AI services
Job Designation
Employee divides their time between in-office and remote work. Access to an office location is required. (Frequency: Minimum 2 days per week; may vary by team but will be weekly in-office expectation)

View full posting on CareerOneStop → ID: 5af1e4f57cdd

Data Scientist

iSpot.tv, INC. · Bellevue, WA

Mid-level Master's

2026-06-02

WA 2026-06-02

Implement industry-standard predictive modeling solutions. Analyze, manipulate, clean, and process large and messy data using predictive modeling solutions and cloud-based computing resources/infrastructure to scale and optimize data science tools and pipelines. Code original R/Python scripts, optim

View full posting on CareerOneStop → ID: 3c086ed88f3e

Data Scientist, PPE Product Intelligence

Amazon · Seattle, WA

Mid-level Bachelor's

2026-06-02

WA 2026-06-02

Requirements

1+ years of data querying languages (e.g. SQL), scripting languages (e.g. Python) or statistical/mathematical software (e.g. R, SAS, Matlab, etc.) experience
2+ years of data/research scientist, statistician or quantitative analyst in an internet-based company with complex and big data sources experience
Bachelor's degree

Preferred

Knowledge of statistical packages and business intelligence tools such as SPSS, SAS, S-PLUS, or R
Experience with clustered data processing (e.g., Hadoop, Spark, Map-reduce, and Hive)

Responsibilities

Design and run rigorous experiments at scale to evaluate and improve foundation model performance across hundreds of millions of products, geographies, and business verticals
Lead the end-to-end lifecycle of evaluation models - from research and experimentation through production launch - including defining success metrics, obtaining stakeholder sign-off, and managing rollout
Conduct online and offline labs to measure the real-world impact of model improvements beyond accuracy, including downstream supply chain, inventory, and financial outcomes
Develop and deploy production-grade statistical models using Python, Scala, SQL, and related tools
Perform large-scale exploratory data analysis to uncover patterns, identify opportunities, and inform model development
Translate complex research findings into clear insights and recommendations for technical and non-technical stakeholders at all levels
No two days look the same, but most will involve some combination of deep technical work, cross-functional collaboration, and scientific thinking at a scale you won't find anywhere else.
You might start the morning reviewing the results of an experiment running across hundreds of millions of products - analyzing whether a new foundation model variant is improving generalization on cold-start items, or whether a novel data generation approach is meaningfully shifting forecast quality. You'll dig into the numbers, form a hypothesis, and design the next iteration.
Later in the day, you could be in a stakeholder review, walking business and engineering partners through a set of launch metrics - explaining not just forecast accuracy, but the downstream supply chain and financial impact your model is driving. Getting a model to production at Amazon requires rigor: you'll define success criteria, run online and offline labs to validate real-world impact, and build the case for sign-off across technical and business stakeholders.
You'll write code - Python, Scala, SQL - to process and analyze data at a scale most scientists never encounter. You'll collaborate closely with scientists, engineers, and business teams, and contribute to research that has a real chance of being published and advancing the field.

View full posting on CareerOneStop → ID: 076ebf6dc450

Machine Learning Engineer, Monetization Engineering

Pinterest, Inc. · Seattle, WA

Mid-level

2026-06-02

WA 2026-06-02

Requirements

2+ years of industry experience applying machine learning methods (e.g., user modeling, personalization, recommender systems, search, ranking, natural language processing, reinforcement learning, and graph representation learning)
Degree in computer science, machine learning, statistics, or related field
End-to-end hands-on experience with building data processing pipelines, large scale machine learning systems, and big data technologies (e.g., Hadoop/Spark)
Practical knowledge of large scale recommender systems, or modern ads ranking, retrieval, targeting, marketplace systems

Preferred

Publications at top ML conferences
Experience using Cursor, Copilot, Codex, or similar AI coding assistants for development, debugging, testing, and refactoring
Familiarity with LLM-powered productivity tools for documentation search, experiment analysis, SQL/data exploration, and engineering workflow acceleration
Expertise in scalable realtime systems that process stream data
Passion for applied ML and the Pinterest product
Background in computational advertising

Responsibilities

Build cutting edge technology using the latest advances in deep learning and machine learning to personalize Pinterest
Partner closely with teams across Pinterest to experiment and improve ML models for various product surfaces (Homefeed, Ads, Growth, Shopping, and Search), while gaining knowledge of how ML works in different areas
Use data driven methods and leverage the unique properties of our data to improve candidates retrieval
Work in a high-impact environment with quick experimentation and product launches
Keep up with industry trends in recommendation systems
Leverage LLMs to enhance content understanding

View full posting on CareerOneStop → ID: 665557491c00

Consultant - Data Science / Data Lake

Deloitte · Seattle, WA

Mid-level Bachelor's

2026-05-31

WA 2026-05-31

Requirements

2+ years of experience in analytics consulting, cybersecurity analytics, security operations, or a combination of these (including internships and in-school experience)
1+ years of experience with artificial intelligence development tools or frameworks such as vector databases, LangChain, or CrewAI
1+ years of experience using Python, Structured Query Language (SQL), R, or SAS to prepare data for analysis, engineer features, visualize data, or support machine learning workflows
Experience working with cybersecurity cloud platforms such as Google SecOps, Amazon Web Services (AWS), or Microsoft Azure, and exposure to security operations center (SOC) threat hunting or incident response
Bachelor's degree in Engineering, Mathematics, Statistics, Computer Science, Cybersecurity, or a field aligned to the role; or 4 years of equivalent professional experience
Ability to travel 50%, on average, based on the work you do and the clients and industries/sectors you serve.
Limited immigration sponsorship may be available.

Preferred

Experience supporting the design, development, or deployment of enterprise data science or artificial intelligence solutions
Experience applying artificial intelligence, machine learning, or advanced data engineering to cybersecurity use cases such as detection engineering or threat response support
Experience parsing and normalizing cyber or information technology telemetry datasets
Experience with PyTorch, Keras, TensorFlow, Scikit-learn, NumPy, or SciPy
Experience with Apache Kafka, Storm, or Spark
Experience creating client-ready materials using Microsoft PowerPoint or Microsoft Visio
The wage range for this role takes into account the wide range of factors that are considered in making compensation decisions including but not limited to skill sets; experience and training; licensure and certifications; and other business and organizational needs. The disclosed range estimate has not been adjusted for the applicable geographic differential associated with the location at which the position may be filled. At Deloitte, it is not typical for an individual to be hired at or near the top of the range for their role and compensation decisions are dependent on the facts and circumstances of each case. A reasonable estimate of the current range is .
You may also be eligible to participate in a discretionary annual incentive program, subject to the rules governing the program, whereby an award, if any, depends on various factors, including, without limitation, individual and organizational performance.

View full posting on CareerOneStop → ID: 3541197cdfca

Data Scientist, PPE Product Intelligence

Amazon · Seattle, WA

Mid-level

2026-05-31

WA 2026-05-31

Requirements

3+ years of data querying languages (e.g. SQL), scripting languages (e.g. Python) or statistical/mathematical software (e.g. R, SAS, Matlab, etc.) experience
2+ years of data scientist experience
3+ years of machine learning/statistical modeling data analysis tools and techniques, and parameters that affect their performance experience
Experience applying theoretical models in an applied environment

Preferred

Experience in Python, Perl, or another scripting language
Experience in a ML or data scientist role with a large technology company

Responsibilities

Design and run rigorous experiments at scale to evaluate and improve foundation model performance across hundreds of millions of products, geographies, and business verticals
Lead the end-to-end lifecycle of evaluation models - from research and experimentation through production launch - including defining success metrics, obtaining stakeholder sign-off, and managing rollout
Conduct online and offline labs to measure the real-world impact of model improvements beyond accuracy, including downstream supply chain, inventory, and financial outcomes
Develop and deploy production-grade statistical models using Python, Scala, SQL, and related tools
Perform large-scale exploratory data analysis to uncover patterns, identify opportunities, and inform model development
Translate complex research findings into clear insights and recommendations for technical and non-technical stakeholders at all levels
No two days look the same, but most will involve some combination of deep technical work, cross-functional collaboration, and scientific thinking at a scale you won't find anywhere else.
You might start the morning reviewing the results of an experiment running across hundreds of millions of products - analyzing whether a new foundation model variant is improving generalization on cold-start items, or whether a novel data generation approach is meaningfully shifting forecast quality. You'll dig into the numbers, form a hypothesis, and design the next iteration.
Later in the day, you could be in a stakeholder review, walking business and engineering partners through a set of launch metrics - explaining not just forecast accuracy, but the downstream supply chain and financial impact your model is driving. Getting a model to production at Amazon requires rigor: you'll define success criteria, run online and offline labs to validate real-world impact, and build the case for sign-off across technical and business stakeholders.
You'll write code - Python, Scala, SQL - to process and analyze data at a scale most scientists never encounter. You'll collaborate closely with scientists, engineers, and business teams, and contribute to research that has a real chance of being published and advancing the field.
The work is hard, the problems are unsolved, and the impact is immediate. If you want to do research that ships - this is where you do it.

View full posting on CareerOneStop → ID: 9904844c860a

Data Scientist

Deloitte · Portland, OR

Mid-level Doctorate

2026-05-30

WA 2026-05-30

Requirements

Bachelor's degree, preferably in Computer Science, Information Technology, Computer Engineering, or related IT discipline; or equivalent experience
5+ Years of Experience in a Data Science or Machine Learning role.
5+ Years of Experience Proficiency in programming languages such as Python or R.
5+ Years of Experience with Strong knowledge of machine learning techniques and algorithms.
5+ Years of Experience with data manipulation and analysis libraries like pandas and NumPy
Limited immigration sponsorship may be available
Ability to travel 10%, on average, based on the work you do and the clients and industries/sectors you serve
Master's or Ph.D. in a relevant field.
Experience with big data technologies like Spark or Hadoop.
Experience with deep learning frameworks like TensorFlow or PyTorch.
Familiarity with cloud platforms such as AWS, Azure, or GCP.
Experience with data visualization tools like Tableau or Power BI.
Analytical/ Decision Making Responsibilities
Analytical ability to manage multiple projects and prioritize tasks into manageable work products
Can operate independently or with minimum supervision
Excellent Written and Communication Skills
Ability to deliver technical demonstrations
The wage range for this role takes into account the wide range of factors that are considered in making compensation decisions including but not limited to skill sets; experience and training; licensure and certifications; and other business and organizational needs. The disclosed range estimate has not been adjusted for the applicable geographic differential associated with the location at which the position may be filled. At Deloitte, it is not typical for an individual to be hired at or near the top of the range for their role and compensation decisions are dependent on the facts and circumstances of each case. A reasonable estimate of the current range is $105,400-207,800
You may also be eligible to participate in a discretionary annual incentive program, subject to the rules governing the program, whereby an award, if any, depends on various factors, including, without limitation, individual and organizational performance.

Responsibilities

Work with stakeholders to identify business problems and formulate them as data science challenges.
Collect, clean, and explore large datasets to uncover trends and patterns.
Develop and train machine learning models to solve problems such as prediction, classification, and clustering.
Validate and deploy models into production environments.
Communicate findings and insights to technical and non-technical audiences through data visualization and presentations.
Stay up to date with the latest trends and technologies in data science and machine learning.
Ability to work independently and collaborate as part of a team
Effective written and verbal communication skills
Meticulous attention to detail and quality of work product
Ability to build and sustain professional relationships
Ability to lead projects or workstreams
Ability to manage and prioritize multiple tasks in a fast-paced and dynamic environment
Strong interpersonal skills and professional demeano
Ability to meet deadlines
Ability to provide clear guidance to others
Communicate regularly with Engagement Managers (Directors), project team members, and representatives from various functional and / or technical teams, including escalating any matters that require additional attention and consideration from engagement management
Independently and collaboratively lead client engagement workstreams focused on improvement, optimization, and transformation of processes including implementing leading practice workflows, addressing deficits in quality, and driving operational outcomes
AI & Engineering leverages cutting-edge engineering capabilities to build, deploy, and operate integrated/verticalized sector solutions in software, data, AI, network, and hybrid cloud infrastructure. These solutions are powered by engineering for business advantage, transforming mission-critical operations. We enable clients to stay ahead with the latest advancements by transforming engineering teams and modernizing technology & data platforms. Our delivery models are tailored to meet each client's unique requirements.
Our AI & Data practice offers comprehensive solutions for designing, developing, and operating advanced Data and AI platforms, products, insights, and services. We help clients innovate, enhance, and manage their data, AI, and analytics capabilities, ensuring they can grow and scale effectively.

View full posting on CareerOneStop → ID: fb47222db27e

Data Scientist

Deloitte · Seattle, WA

Mid-level Doctorate

2026-05-30

WA 2026-05-30

Requirements

Bachelor's degree, preferably in Computer Science, Information Technology, Computer Engineering, or related IT discipline; or equivalent experience
5+ Years of Experience in a Data Science or Machine Learning role.
5+ Years of Experience Proficiency in programming languages such as Python or R.
5+ Years of Experience with Strong knowledge of machine learning techniques and algorithms.
5+ Years of Experience with data manipulation and analysis libraries like pandas and NumPy
Limited immigration sponsorship may be available
Ability to travel 10%, on average, based on the work you do and the clients and industries/sectors you serve
Master's or Ph.D. in a relevant field.
Experience with big data technologies like Spark or Hadoop.
Experience with deep learning frameworks like TensorFlow or PyTorch.
Familiarity with cloud platforms such as AWS, Azure, or GCP.
Experience with data visualization tools like Tableau or Power BI.
Analytical/ Decision Making Responsibilities
Analytical ability to manage multiple projects and prioritize tasks into manageable work products
Can operate independently or with minimum supervision
Excellent Written and Communication Skills
Ability to deliver technical demonstrations
The wage range for this role takes into account the wide range of factors that are considered in making compensation decisions including but not limited to skill sets; experience and training; licensure and certifications; and other business and organizational needs. The disclosed range estimate has not been adjusted for the applicable geographic differential associated with the location at which the position may be filled. At Deloitte, it is not typical for an individual to be hired at or near the top of the range for their role and compensation decisions are dependent on the facts and circumstances of each case. A reasonable estimate of the current range is $105,400-207,800
You may also be eligible to participate in a discretionary annual incentive program, subject to the rules governing the program, whereby an award, if any, depends on various factors, including, without limitation, individual and organizational performance.

Responsibilities

Work with stakeholders to identify business problems and formulate them as data science challenges.
Collect, clean, and explore large datasets to uncover trends and patterns.
Develop and train machine learning models to solve problems such as prediction, classification, and clustering.
Validate and deploy models into production environments.
Communicate findings and insights to technical and non-technical audiences through data visualization and presentations.
Stay up to date with the latest trends and technologies in data science and machine learning.
Ability to work independently and collaborate as part of a team
Effective written and verbal communication skills
Meticulous attention to detail and quality of work product
Ability to build and sustain professional relationships
Ability to lead projects or workstreams
Ability to manage and prioritize multiple tasks in a fast-paced and dynamic environment
Strong interpersonal skills and professional demeano
Ability to meet deadlines
Ability to provide clear guidance to others
Communicate regularly with Engagement Managers (Directors), project team members, and representatives from various functional and / or technical teams, including escalating any matters that require additional attention and consideration from engagement management
Independently and collaboratively lead client engagement workstreams focused on improvement, optimization, and transformation of processes including implementing leading practice workflows, addressing deficits in quality, and driving operational outcomes
AI & Engineering leverages cutting-edge engineering capabilities to build, deploy, and operate integrated/verticalized sector solutions in software, data, AI, network, and hybrid cloud infrastructure. These solutions are powered by engineering for business advantage, transforming mission-critical operations. We enable clients to stay ahead with the latest advancements by transforming engineering teams and modernizing technology & data platforms. Our delivery models are tailored to meet each client's unique requirements.
Our AI & Data practice offers comprehensive solutions for designing, developing, and operating advanced Data and AI platforms, products, insights, and services. We help clients innovate, enhance, and manage their data, AI, and analytics capabilities, ensuring they can grow and scale effectively.

View full posting on CareerOneStop → ID: 40c16c089c03

Data Scientist

Deloitte · Bellevue, WA

Mid-level Doctorate

2026-05-30

WA 2026-05-30

Requirements

Bachelor's degree, preferably in Computer Science, Information Technology, Computer Engineering, or related IT discipline; or equivalent experience
5+ Years of Experience in a Data Science or Machine Learning role.
5+ Years of Experience Proficiency in programming languages such as Python or R.
5+ Years of Experience with Strong knowledge of machine learning techniques and algorithms.
5+ Years of Experience with data manipulation and analysis libraries like pandas and NumPy
Limited immigration sponsorship may be available
Ability to travel 10%, on average, based on the work you do and the clients and industries/sectors you serve
Master's or Ph.D. in a relevant field.
Experience with big data technologies like Spark or Hadoop.
Experience with deep learning frameworks like TensorFlow or PyTorch.
Familiarity with cloud platforms such as AWS, Azure, or GCP.
Experience with data visualization tools like Tableau or Power BI.
Analytical/ Decision Making Responsibilities
Analytical ability to manage multiple projects and prioritize tasks into manageable work products
Can operate independently or with minimum supervision
Excellent Written and Communication Skills
Ability to deliver technical demonstrations
The wage range for this role takes into account the wide range of factors that are considered in making compensation decisions including but not limited to skill sets; experience and training; licensure and certifications; and other business and organizational needs. The disclosed range estimate has not been adjusted for the applicable geographic differential associated with the location at which the position may be filled. At Deloitte, it is not typical for an individual to be hired at or near the top of the range for their role and compensation decisions are dependent on the facts and circumstances of each case. A reasonable estimate of the current range is $105,400-207,800
You may also be eligible to participate in a discretionary annual incentive program, subject to the rules governing the program, whereby an award, if any, depends on various factors, including, without limitation, individual and organizational performance.

Responsibilities

Work with stakeholders to identify business problems and formulate them as data science challenges.
Collect, clean, and explore large datasets to uncover trends and patterns.
Develop and train machine learning models to solve problems such as prediction, classification, and clustering.
Validate and deploy models into production environments.
Communicate findings and insights to technical and non-technical audiences through data visualization and presentations.
Stay up to date with the latest trends and technologies in data science and machine learning.
Ability to work independently and collaborate as part of a team
Effective written and verbal communication skills
Meticulous attention to detail and quality of work product
Ability to build and sustain professional relationships
Ability to lead projects or workstreams
Ability to manage and prioritize multiple tasks in a fast-paced and dynamic environment
Strong interpersonal skills and professional demeano
Ability to meet deadlines
Ability to provide clear guidance to others
Communicate regularly with Engagement Managers (Directors), project team members, and representatives from various functional and / or technical teams, including escalating any matters that require additional attention and consideration from engagement management
Independently and collaboratively lead client engagement workstreams focused on improvement, optimization, and transformation of processes including implementing leading practice workflows, addressing deficits in quality, and driving operational outcomes
AI & Engineering leverages cutting-edge engineering capabilities to build, deploy, and operate integrated/verticalized sector solutions in software, data, AI, network, and hybrid cloud infrastructure. These solutions are powered by engineering for business advantage, transforming mission-critical operations. We enable clients to stay ahead with the latest advancements by transforming engineering teams and modernizing technology & data platforms. Our delivery models are tailored to meet each client's unique requirements.
Our AI & Data practice offers comprehensive solutions for designing, developing, and operating advanced Data and AI platforms, products, insights, and services. We help clients innovate, enhance, and manage their data, AI, and analytics capabilities, ensuring they can grow and scale effectively.

View full posting on CareerOneStop → ID: b2b19730a972

Machine Learning Research Scientist - Health AIML

Apple · Seattle, WA

Mid-level Doctorate

2026-05-30

WA 2026-05-30

Requirements

PhD in Computer Science/Engineering, Machine Learning, Statistics, Mathematics or related field.
Industry work experience.
Experience landing contributions to major LLM training runs.
Proven track record of publishing SOTA.
Strong skills with deep learning frameworks such as PyTorch, JAX, or TensorFlow.

Preferred

Experience in training and evaluating multimodal models.
Understand of time-series modeling, self-supervised learning, and cross-modal training.
Ability to thoroughly evaluate and improve deep learning architectures in a self-directed fashion.
Motivated by safely deploying LLMs in the health and fitness space.

Responsibilities

The Health AIML team is at the forefront of machine learning and health science at Apple. We are a close-knit team of research scientists, software engineers and machine learning engineers passionate about delivering innovative technologies that impact millions of users. We are looking for a Machine Learning Research Scientist with strong dedication to solving real-world problems in health and fitness that enrich our customers' lives.
We're developing next-generation multimodal models to create intelligent health and fitness experiences. This role requires someone with strong expertise in large multimodal models to work at the intersection of AI and health to build foundational models that scale to billions of users worldwide. Your work will shape the future of health and fitness technologies at Apple. We are looking for a senior researcher to guide multimodality research. You will focus on the development of foundational technology that enables models to understand health and fitness data.

View full posting on CareerOneStop → ID: 49ac6db33d5f

Data Scientist

Deloitte · Boise, ID

Mid-level Doctorate

2026-05-30

ID 2026-05-30

Requirements

Bachelor's degree, preferably in Computer Science, Information Technology, Computer Engineering, or related IT discipline; or equivalent experience
5+ Years of Experience in a Data Science or Machine Learning role.
5+ Years of Experience Proficiency in programming languages such as Python or R.
5+ Years of Experience with Strong knowledge of machine learning techniques and algorithms.
5+ Years of Experience with data manipulation and analysis libraries like pandas and NumPy
Limited immigration sponsorship may be available
Ability to travel 10%, on average, based on the work you do and the clients and industries/sectors you serve
Master's or Ph.D. in a relevant field.
Experience with big data technologies like Spark or Hadoop.
Experience with deep learning frameworks like TensorFlow or PyTorch.
Familiarity with cloud platforms such as AWS, Azure, or GCP.
Experience with data visualization tools like Tableau or Power BI.
Analytical/ Decision Making Responsibilities
Analytical ability to manage multiple projects and prioritize tasks into manageable work products
Can operate independently or with minimum supervision
Excellent Written and Communication Skills
Ability to deliver technical demonstrations
The wage range for this role takes into account the wide range of factors that are considered in making compensation decisions including but not limited to skill sets; experience and training; licensure and certifications; and other business and organizational needs. The disclosed range estimate has not been adjusted for the applicable geographic differential associated with the location at which the position may be filled. At Deloitte, it is not typical for an individual to be hired at or near the top of the range for their role and compensation decisions are dependent on the facts and circumstances of each case. A reasonable estimate of the current range is $105,400-207,800
You may also be eligible to participate in a discretionary annual incentive program, subject to the rules governing the program, whereby an award, if any, depends on various factors, including, without limitation, individual and organizational performance.

Responsibilities

Work with stakeholders to identify business problems and formulate them as data science challenges.
Collect, clean, and explore large datasets to uncover trends and patterns.
Develop and train machine learning models to solve problems such as prediction, classification, and clustering.
Validate and deploy models into production environments.
Communicate findings and insights to technical and non-technical audiences through data visualization and presentations.
Stay up to date with the latest trends and technologies in data science and machine learning.
Ability to work independently and collaborate as part of a team
Effective written and verbal communication skills
Meticulous attention to detail and quality of work product
Ability to build and sustain professional relationships
Ability to lead projects or workstreams
Ability to manage and prioritize multiple tasks in a fast-paced and dynamic environment
Strong interpersonal skills and professional demeano
Ability to meet deadlines
Ability to provide clear guidance to others
Communicate regularly with Engagement Managers (Directors), project team members, and representatives from various functional and / or technical teams, including escalating any matters that require additional attention and consideration from engagement management
Independently and collaboratively lead client engagement workstreams focused on improvement, optimization, and transformation of processes including implementing leading practice workflows, addressing deficits in quality, and driving operational outcomes
AI & Engineering leverages cutting-edge engineering capabilities to build, deploy, and operate integrated/verticalized sector solutions in software, data, AI, network, and hybrid cloud infrastructure. These solutions are powered by engineering for business advantage, transforming mission-critical operations. We enable clients to stay ahead with the latest advancements by transforming engineering teams and modernizing technology & data platforms. Our delivery models are tailored to meet each client's unique requirements.
Our AI & Data practice offers comprehensive solutions for designing, developing, and operating advanced Data and AI platforms, products, insights, and services. We help clients innovate, enhance, and manage their data, AI, and analytics capabilities, ensuring they can grow and scale effectively.

View full posting on CareerOneStop → ID: 9f4391ee3526

Data Scientist - 3035128

Apex Systems, Inc. · Redmond, WA

Mid-level

2026-05-30

WA 2026-05-30

Requirements

5 years of experience in data analytics.
5 years of experience with SQL, bonus if familiar with SparkSQL, Databricks, or Azure Data Explorer.
2 years of experience with dashboarding tools, PowerBI preferred.
Proficient in Python, bonus if familiar with PySpark.
Able to work in a collaborative, diverse and fast-paced team.
Excellent analytical, and problem-solving skills and autonomy when faced with solving data problems.
Excellent verbal, visual and written communication skills.
Interest in games, bonus if experience in gaming industry.
Local to Seattle area.

Responsibilities

We are seeking a Data Scientist who is passionate about delivering high-impact, high-quality results to join the Player Data and Insights team. In this role, you will drive insights that inform the Game Studio strategy, with a focus on Consumer Products, Out of Game Experiences and Partnerships. You'll collaborate closely with the stakeholder teams to enhance consumer products reporting, analyze out of game experiences, evaluate opportunities, and recommend data-drive strategies to level up the connection between all parts of the franchise. This role is additional coverage for a team member on maternity leave, and you will be taking over additional duties beyond this specific scope as needed. These include maintaining forecasting models, assisting in franchise reporting and estimation, and collaborating with other data science vendors in the Beyond the Game space. Specific responsibilities include making recommendations to optimize business performance and evaluating the impact of various programs and initiatives on critical metrics, including tying out of game activities to in-game metrics. The ideal candidate will have experience with statistical analysis, data visualization tools, and strong communication skills to translate insights into actionable recommendations for both technical and non-technical stakeholders.
Partner with Consumer Products team and PADI data engineering to turn our Consumer Products data into clear reporting and actionable insights.
Identify key learnings from your analysis and synthesize them into recommendations for stakeholders.
Work collaboratively with other PADI data scientists to incorporate Beyond the Game findings into relevant major analyses and franchise beats.
Conduct data analysis as requested for stakeholder groups across Partnerships, Marketing and Consumer Products, including understanding ROI of out-of-game initiatives and optimizing for in-game metrics.
Be self-driven and show ability to deliver on ambiguous projects with incomplete or dirty data.
Maintain dashboards in PowerBI that enable stakeholders to understand the business and supporting onboarding to other self-service tools
Manipulate and analyze complex, high-volume, high-dimensionality data from varying sources using a variety of tools and data analysis techniques.

View full posting on CareerOneStop → ID: 0e84a5b54ed6

Data Scientist, Demand Forecasting

Amazon · Bellevue, WA

Mid-level Bachelor's

2026-05-29

WA 2026-05-29

Requirements

1+ years of data querying languages (e.g. SQL), scripting languages (e.g. Python) or statistical/mathematical software (e.g. R, SAS, Matlab, etc.) experience
2+ years of data/research scientist, statistician or quantitative analyst in an internet-based company with complex and big data sources experience
Bachelor's degree

Preferred

Knowledge of statistical packages and business intelligence tools such as SPSS, SAS, S-PLUS, or R
Experience with clustered data processing (e.g., Hadoop, Spark, Map-reduce, and Hive)

Responsibilities

Design and run rigorous experiments at scale to evaluate and improve foundation model performance across hundreds of millions of products, geographies, and business verticals
Lead the end-to-end lifecycle of forecasting models - from research and experimentation through production launch - including defining success metrics, obtaining stakeholder sign-off, and managing rollout
Conduct online and offline labs to measure the real-world impact of forecast improvements beyond accuracy, including downstream supply chain, inventory, and financial outcomes
Develop and deploy production-grade deep learning and statistical models using Python, Scala, SQL, and related tools
Perform large-scale exploratory data analysis to uncover patterns, identify opportunities, and inform model development
Translate complex research findings into clear insights and recommendations for technical and non-technical stakeholders at all levels
Contribute to Amazon's scientific community and the broader research field through collaboration and publication in top-tier venues
No two days look the same, but most will involve some combination of deep technical work, cross-functional collaboration, and scientific thinking at a scale you won't find anywhere else.
You might start the morning reviewing the results of an experiment running across hundreds of millions of products - analyzing whether a new foundation model variant is improving generalization on cold-start items, or whether a novel data generation approach is meaningfully shifting forecast quality. You'll dig into the numbers, form a hypothesis, and design the next iteration.
Later in the day, you could be in a stakeholder review, walking business and engineering partners through a set of launch metrics - explaining not just forecast accuracy, but the downstream supply chain and financial impact your model is driving. Getting a model to production at Amazon requires rigor: you'll define success criteria, run online and offline labs to validate real-world impact, and build the case for sign-off across technical and business stakeholders.
You'll write code - Python, Scala, SQL - to process and analyze data at a scale most scientists never encounter. You'll collaborate closely with scientists, engineers, and business teams, and contribute to research that has a real chance of being published and advancing the field.
The work is hard, the problems are unsolved, and the impact is immediate. If you want to do research that ships - this is where you do it.
Amazon offers a full range of benefits that support you and eligible family members, including domestic partners and their children. Benefits can vary by location, the number of regularly scheduled hours you work, length of employment, and job status such as seasonal or temporary employment.
The benefits that generally apply to regular, full-time employees include:
Medical, Dental, and Vision Coverage
Maternity and Parental Leave Options
Paid Time Off (PTO)
If you are not sure that every qualification on the list above describes you exactly, we'd still love to hear from you!
At Amazon, we value people with unique backgrounds, experiences, and skillsets. If you're passionate about this role and want to make an impact on a global scale, please apply!

View full posting on CareerOneStop → ID: db6094b0d370

Machine Learning Engineer, Level 4

Snap Inc. · Seattle, WA

Mid-level Doctorate

2026-05-29

WA 2026-05-29

Requirements

Bachelor's Degree in a relevant technical field such as computer science or equivalent years of practical work experience
3+ years of post-Bachelor's machine learning experience; or Master's degree in a technical field + 2+ year of post-grad machine learning experience; or PhD in a relevant technical field
Experience developing machine learning models for ranking, recommendations, search, content understanding, image generation, or other relevant applications of machine learning

Preferred

Advanced degree in computer science or related field
Experience working with machine learning frameworks such as TensorFlow, Caffe2, PyTorch, Spark ML, scikit-learn, or related frameworks
Experience working with machine learning, ranking infrastructures, and system design

Responsibilities

Build and deploy machine learning models that power core products, serving millions of Snapchatters
Apply modern ML techniques to solve large-scale, real-world problems
Own the full ML lifecycle from data analysis to production deployment
Partner with cross-functional teams to prototype and launch ML-driven features
Utilize AI tools to design and ship scalable services while upholding rigorous standards for code correctness, security, and production
Knowledge, Skills & Abilities:
Strong understanding of machine learning approaches and algorithms
Able to prioritize duties and work well on your own
Ability to work with both internal and external partners
Skilled at solving open ambiguous problems
Strong collaboration and mentorship skills
Proficiency in, or a strong aptitude for, leveraging AI tools to streamline development, paired with the critical judgment to audit generated output for architectural integrity, performance bottlenecks, and security risks
Adaptability in learning and applying evolving AI systems and tools to remain at the forefront of engineering trends and modern development practices

View full posting on CareerOneStop → ID: 3c9d2da8f510

Machine Learning Engineer, Level 4

Snap Inc. · Bellevue, WA

Mid-level Doctorate

2026-05-29

WA 2026-05-29

Requirements

Bachelor's Degree in a relevant technical field such as computer science or equivalent years of practical work experience
3+ years of post-Bachelor's machine learning experience; or Master's degree in a technical field + 2+ year of post-grad machine learning experience; or PhD in a relevant technical field
Experience developing machine learning models for ranking, recommendations, search, content understanding, image generation, or other relevant applications of machine learning

Preferred

Advanced degree in computer science or related field
Experience working with machine learning frameworks such as TensorFlow, Caffe2, PyTorch, Spark ML, scikit-learn, or related frameworks
Experience working with machine learning, ranking infrastructures, and system design

Responsibilities

Build and deploy machine learning models that power core products, serving millions of Snapchatters
Apply modern ML techniques to solve large-scale, real-world problems
Own the full ML lifecycle from data analysis to production deployment
Partner with cross-functional teams to prototype and launch ML-driven features
Utilize AI tools to design and ship scalable services while upholding rigorous standards for code correctness, security, and production
Knowledge, Skills & Abilities:
Strong understanding of machine learning approaches and algorithms
Able to prioritize duties and work well on your own
Ability to work with both internal and external partners
Skilled at solving open ambiguous problems
Strong collaboration and mentorship skills
Proficiency in, or a strong aptitude for, leveraging AI tools to streamline development, paired with the critical judgment to audit generated output for architectural integrity, performance bottlenecks, and security risks
Adaptability in learning and applying evolving AI systems and tools to remain at the forefront of engineering trends and modern development practices

View full posting on CareerOneStop → ID: 357ea433c4b5

Business Data Scientist, Ads Marketing Analytics

Google · Kirkland, WA

Mid-level Doctorate

2026-05-28

WA 2026-05-28

Requirements

Master's degree in a quantitative field (Statistics, Mathematics, Data Science, Bioinformatics, Economics, etc.) or equivalent practical experience
3 years of experience in a data science field.
Experience with statistical software (e.g., R, Python, MATLAB) and database languages (i.e., SQL).
Experience using analytics to solve product or business problems, querying databases or statistical analysis.

Preferred

PhD in Statistics or related quantitative discipline.
2 years of experience, including statistical data analysis such as generalized linear models, multivariate analysis, clustering/segmentation and sampling methods.
Experience in controlled experiment design and causal inference methods.
Ability to prioritize requests and partner well in an environment with competing demands from stakeholders.
Ability to convince business stakeholders and communicate analysis insights to non-technical audiences and willingness to both teach others and learn new techniques.
Excellent communication and team-work including problem-solving skills.

Responsibilities

Google's leadership team hand-picks thorny business challenges, and members of BizOps work in small teams to find solutions. As part of this team you fully immerse yourself in data collection, draw insight from analysis, and then zoom out to develop compelling, synthesized recommendations. Taking strategy one step further, you also persuasively communicate your recommendations to senior-level executives, roll-up your sleeves to help drive implementation and check back-in to see the impact of your recommendations.
Google Ads Marketing helps advertisers of all sizes succeed with digital marketing. In this role, you will work with a team to advance marketing science for customers using Google's advertising solutions. This unique opportunity applies Data Science tools to accelerate Ads business growth, working cross-functionally with Sales, Marketing, and Product teams.
As a Data Scientist on this team, you will perform deep data analytics, drive experimentation and measurement, and advance machine learning modeling to support global marketing programs.
Collaborating with a multidisciplinary team of marketers, product managers, data scientists, and engineers, you will leverage underlying data to align on key metrics and methodologies. Your insights will enable marketers to develop highly effective programs. Using core Data Science expertise, you will design, prototype, and build scalable analysis pipelines to support campaigns. You will perform analytics, execute experimentation, and conduct incrementality measurement to inform strategic decisions across the entire Ads Marketing lifecycle-from acquisition and onboarding to growth and retention.
You will build investigative frameworks and measurement capabilities to generate data-driven insights that drive business growth. You will effectively communicate your investigative results to marketing partners and leadership to inform critical decision-making.
The US base salary range for this full-time position is $138,000-$198,000 + bonus + equity + benefits. Our salary ranges are determined by role, level, and location. Within the range, individual pay is determined by work location and additional factors, including job-related skills, experience, and relevant education or training. Your recruiter can share more about the specific salary range for your preferred location during the hiring process.
Please note that the compensation details listed in US role postings reflect the base salary only, and do not include bonus, equity, or benefits. Learn more aboutbenefits at Google (https://careers.google.com/benefits/) .
Work with large, complex data sets. Solve analysis problems, applying advanced investigative methods (such as statistical and machine learning models) as needed. Conduct analysis that includes problem formulation, data gathering and requirements specification, processing, analysis, ongoing deliverables, and presentations.
Design and analyze controlled experiments or counterfactual causal inference studies to examine the incremental impact of Ads marketing programs.
Build and prototype analysis pipelines iteratively to provide insights at scale. Develop comprehensive knowledge of Google data structures and metrics, advocating for changes where needed.
Interact cross-functionally, making business recommendations (e.g. cost-benefit, forecasting, experiment analysis) with effective presentations of findings at multiple levels of stakeholders through visual displays of quantitative information.
Develop and automate reports, iteratively build and prototype dashboards to provide insights at scale, solving for business priorities.
Information collected and processed as part of your Google Careers profile, and any job applications you choose to submit is subject to Google'sApplicant and Candidate Privacy Policy (./privacy-policy) .

View full posting on CareerOneStop → ID: 8bedd46a44c4

Data Scientist II, Middle Mile Transportation Science team

Amazon · Bellevue, WA

Mid-level Master's

2026-05-28

WA 2026-05-28

Requirements

Master's degree in Science, Technology, Engineering, or Mathematics (STEM)
2+ years of data querying languages (e.g. SQL), scripting languages (e.g. Python) or statistical/mathematical software (e.g. R, SAS, Matlab, etc.) experience
2+ years of machine learning/statistical modeling data analysis tools and techniques, and parameters that affect their performance experience
Experience with AWS services including S3, Redshift, Sagemaker, EMR, Kinesis, Lambda, and EC2
Proficiency in statistical modeling and machine learning - time-series forecasting, regression, tree-based methods, and deep learning.
Demonstrated ability to communicate technical results to non-technical business audiences.

Preferred

3+ years of data querying languages (e.g. SQL), scripting languages (e.g. Python) or statistical/mathematical software (e.g. R, SAS, Matlab, etc.) experience
3+ years of machine learning/statistical modeling data analysis tools and techniques, and parameters that affect their performance experience

Responsibilities

Design and implement complex ML and optimization solutions (forecasting, MIP/LP, simulation, Deep learning / foundation model);
Drive end-to-end delivery of scalable models - from data exploration and feature engineering through training, evaluation, deployment, and post-launch monitoring;
Develop new modeling patterns and analytical frameworks for forecasting (multivariate, hierarchical, causal-DAG, model-chaining) and optimization;
Build robust model validation, backtesting, and monitoring pipelines; identify and eliminate sources of leakage, bias, and silent failure;
Define and own model performance metrics (e.g., WAPE) tied to business outcomes;
Partner with Data Engineering and Software Development to productionize models and define I/O contracts, packaging, and model CI/CD;
Excellent communication to present findings, tradeoffs, and recommendations clearly to stakeholders and senior leadership.

View full posting on CareerOneStop → ID: d4f4fd89e4ba

AI/ML Engineer

Raft LLC · Tacoma, WA

Mid-level Doctorate

2026-05-28

WA 2026-05-28

Requirements

3+ years of relevant hands-on experience, or a PhD in a related field with demonstrated practical application
Practical experience in Machine Learning models and Software Engineering
A passion for (and track record of) innovation, an interest in exploring and leveraging new data modalities, and working across interdisciplinary teams
Experience building and maintaining machine learning platforms and pipelines
Experience in building machine learning models, and
Experience in using data processing frameworks (Apache Spark preferred)
Practical programming and scripting skills (Python preferred)
Fast learner, analytical thinker, creative, hands-on, strong communication skills
Able to work both independently and as part of a team
Excellent problem-solving skills and attention to detail.
Proven experience with modern software development and engineering practices including scrum/agile, Git, and DevOps
Obtain Security+ within the first 90 days of employment with Raft
Ability to obtaina Top Secret clearance with potential for SCI

Preferred

Publications or GitHub repos showcasing your skills

Education

Annual budget for your tech/gadgets needs
Generous Referral Bonuses
Annual budget for your tec

Responsibilities

*AI/ML Engineer,
you will collaborate with a cross-functional data team comprising of DevSecOps engineers, Product Owners, Data Engineers and Data Scientists. Your primary responsibility will be to develop machine learning models that are integral to a larger pipeline delivering value to our end customers.

View full posting on CareerOneStop → ID: 754c9024cb6a

Machine Learning Engineer, AWS Applied AI Solution

Amazon · Seattle, WA

Mid-level Bachelor's

2026-05-27

WA 2026-05-27

Requirements

3+ years of non-internship professional software development experience
2+ years of non-internship design or architecture (design patterns, reliability and scaling) of new and existing systems experience
1+ years of software development engineer or related occupational experience
1+ years of designing and developing large-scale, multi-tiered, multi-threaded, embedded or distributed software applications, tools, systems, and services using: C#, C++, Java, or Perl experience
1+ years of Object Oriented Design experience
Bachelor's degree or foreign equivalent in Computer Science, Engineering, Mathematics, or a related field
Experience programming with at least one software programming language

Preferred

3+ years of full software development life cycle, including coding standards, code reviews, source control management, build processes, testing, and operations experience
Bachelor's degree in computer science or equivalent

Responsibilities

Work closely with Applied Scientists and cross-functional engineering teams to transform research code into robust, scalable production systems
Own end-to-end deployment at scale of Generative AI and ML methods, ensuring reliability and performance
Establish scalable, efficient, automated processes for large-scale data analysis, machine learning model development, model validation and serving
Research and implement innovative approaches for efficient model deployment, training, and optimization
Document processes and methods for both technical and non-technical audiences, ensuring knowledge transfer and best practices
Contribute to code reviews and maintain high engineering standards across the team
Mentor junior MLEs and actively participate in recruiting top talent to grow
Present outcomes and explain technical approaches to senior leadership, translating complex concepts into business impact

View full posting on CareerOneStop → ID: bad8b55da3c4

Data Scientist, Product

OpenAI Inc. · Seattle, WA

Mid-level

2026-05-25

WA 2026-05-25

Responsibilities

As a Data Scientist on the Applied Product team, you will contribute to a data-driven product development culture for consumer and enterprise products at OpenAI. This is critical as our products reach millions of users and businesses worldwide. We are focused on aligning both research and product development to drive measurable impact for these individuals and organizations alike.
You should expect to define our north-star metrics, design A/B tests, and establish source-of-truth dashboards that the entire company can use to answer their own product questions. Most importantly, you should expect to be a core member of the product development team.
This role is based in San Francisco, CA or Seattle, WA. We use a hybrid work model of 3 days in the office per week and offer relocation assistance to new employees.
*In this role, you will:
Embed with the product development team as a trusted partner, uncovering new ways to improve the product and drive growth
Define and interpret A/B tests that help answer critical questions about the impact of model and UX changes to our product
Establish a data-driven product development culture by defining, tracking, and operationalizing feature-, product-, and company-level metrics
Develop and socialize dashboards, reports, and other ways of enabling the team and company to answer product data questions in a self-serve way
*You might thrive in this role if you have:
5+ years experience in a quantitative role navigating highly ambiguous environments, ideally as an early data scientist or product analyst at a hyper-growth product company or research org
Proposed, designed, and run rigorous experiments with clear insights and product recommendations utilizing SQL and Python
Defined, implemented, and operationalized new feature and product-level metrics from scratch
Excellent communication skills with demonstrated ability to communicate with product managers, engineers, and executives alike
Strategic insights beyond the paradigm of statistical significance testing
*You could be an especially great fit if you have:
Strong programming background, with ability to run simulations and prototype variants
Experience validating quantitative insights with qualitative methods (e.g. surveys, UXR)
Demonstrated prior experience in NLP, large language models, or generative AI

View full posting on CareerOneStop → ID: 382a92856766

Data Scientist

Actalent · Seattle, WA

Mid-level Doctorate

2026-05-23

WA 2026-05-23

Requirements

Hands-on expertise with cutting-edge molecular biology, microbiology, and/or biochemistry methods and concepts.
Familiarity with data analysis tools and methodologies commonly used in modern laboratory data analysis.
5+ years of experience as a data scientist or in a similar role involving data extraction, analysis, statistical modeling, and communication.
5+ years of experience with data querying languages such as SQL.
5+ years of experience with scripting languages such as Python.
5+ years of experience with statistical or mathematical software such as R, SAS, or MATLAB.
Experience with statistical models, including multinomial logistic regression.
Experience building and working with data pipelines.
Demonstrated ability to work successfully within an entrepreneurial environment.
Excellent organizational skills with strong attention to detail and meticulous record keeping.
Strong verbal and written communication skills for technical and non-technical audiences.
Knowledge of safety procedures related to operation of laboratory equipment and handling of chemical and biological hazards.
Master's degree in a quantitative field such as statistics, mathematics, data science, business analytics, economics, finance, engineering, or computer science, or a Bachelor's degree with 8+ years of professional or military experience.

Preferred

PhD degree in a life science discipline such as Biochemistry, Genetics, Molecular Biology, or Microbiology, with 8-10 years of directly related commercial experience.
Ability to work effectively within multidisciplinary teams at the interface of life science and computer science.
Broad familiarity with different areas of the life sciences and their experimental approaches.
Hands-on experience in high-throughput research, including operation of liquid handling systems.
2+ years of experience with data visualization tools such as AWS QuickSight, Tableau, or R Shiny.
Experience using AWS and related cloud-based tools in support of data pipelines and analytics.
Experience serving as a leader and mentor on a data science team, supporting the development of colleagues' technical and analytical skills.

Responsibilities

Execute existing laboratory workflows from experimental planning through data analysis, ensuring accuracy, reproducibility, and timely completion of work.
Recognize, document, and escalate protocol deviations to relevant stakeholders, and contribute to corrective and preventive actions.
Ensure laboratory equipment and instruments remain in good operating condition, identify malfunctions, and perform or coordinate troubleshooting as needed.
Maintain an up-to-date understanding of laboratory methods, protocols, and analytical techniques used in the lab.
Provide structured feedback on laboratory workflows and participate in developing solutions to process bottlenecks, throughput limitations, and data quality issues.
Work with a team of researchers to extend, refine, and interpret advanced analytical methodologies in the life sciences.
Facilitate effective interactions with internal and external collaborators to improve efficiency and implementation of cutting-edge analytical methods.
Adapt to unexpected schedule changes and respond to urgent or emergency situations in the laboratory environment as needed.
Extract, clean, and analyze complex datasets using data querying and scripting languages, and build statistical models to support scientific and business decisions.
Develop, implement, and maintain robust data pipelines that support laboratory workflows and analytical processes.
Apply statistical and machine learning models, such as multinomial logistic regression, to derive insights from experimental and operational data.
Create clear, insightful visualizations and reports using data visualization tools to communicate findings to technical and non-technical stakeholders.
Communicate results, methods, and recommendations clearly in both written and verbal form, tailoring the level of detail to the audience.
Act as a leader and mentor within the data science function, guiding colleagues on best practices in data extraction, analysis, modeling, and communication.
Ensure adherence to laboratory safety procedures, including proper operation of laboratory equipment and safe handling of chemical and biological hazards.

View full posting on CareerOneStop → ID: c817b8fb9e7f

Data Scientist III

Indeed · Seattle, WA

Mid-level Doctorate

2026-05-23

WA 2026-05-23

Responsibilities

As a Data Scientist III at Indeed, you will leverage your expertise in data science, statistics, AI and machine learning to take on complex product, marketing and business challenges. You will design and implement analytical solutions that guide decisions, optimize product performance or marketing campaigns, and create measurable impact across the organization.
You will work closely with engineering and product or marketing teams to identify opportunities, evaluate initiatives, and develop models and analyses that inform data-driven strategies. You will also contribute to building best practices in data science and mentor others in the team, helping elevate the technical capabilities and impact of those around you.
Oversee the design and execution of advanced analyses, experiments, and machine learning models to address complex questions.
Translate data into actionable insights to guide product, marketing and business decisions.
Develop and maintain scalable, robust data pipelines and models for large-scale product data. Collaborate with engineering and product teams to integrate data science solutions into product workflows.
Mentor and support other data scientists, promoting knowledge sharing and best practices.
Contribute to the development of AI agents and skills, methodologies, and processes that improve the efficiency and impact of the data science team.
Communicate findings clearly through presentations, visualizations, and documentation for diverse audiences.
*Skills/Competencies
Requires a Bachelor's degree in Computer Science, Mathematics, or Statistics, and a minimum of 8 years of related experience; or a Master's degree with a minimum of 6 years of experience; or a PhD with 3 years experience
Expertise in A/B testing and experimentation is required
Solid foundation in data science methods and technologies.
Able to influence technical direction and contribute to long-term planning.
Able to work effectively with other teams and mentor colleagues.
Focused on delivering high-quality, impactful solutions that contribute to business goals.
Excellent written and verbal communication in English, effective with technical and business audiences.

View full posting on CareerOneStop → ID: 01370a76aa69

Data Scientist III - AMZ9442729

Amazon · Seattle, WA

Mid-level Bachelor's

2026-05-23

WA 2026-05-23

Requirements

Bachelor's degree or foreign equivalent degree in Statistics, Applied Mathematics, Economics, Engineering, Computer Science or a related field and two years of experience in the job offered or a related occupation. Employer will accept four years of experience as equivalent to the Bachelor's degree and two years of experience. Must have one year of experience in the following skills: (1) building statistical models and machine learning models using large datasets from multiple resources; (2) building complex data analyses by leveraging scripting languages including Python, Java, or related scripting language; and (3) communicating with users, technical teams, and management to collect requirements, evaluate alternatives, and develop processes and tools to support the organization.

Preferred

Please see job description and the position requirements above.

Responsibilities

Own the data science elements of various products to help with data-based decision making, product performance optimization, and product performance tracking. Work directly with product managers to help drive the design of the product. Work with Technical Product Managers to help drive the build planning. Translate business problems and products into data requirements and metrics. Initiate the design, development, and implementation of scientific analysis projects or deliverables. Own the analysis, modelling, system design, and development of data science solutions for products. Write documents and make presentations that explain model/analysis results to the business. Bridge the degree of uncertainty in both problem definition and data scientific solution approaches. Build consensus on data, metrics, and analysis to drive business and system strategy.

View full posting on CareerOneStop → ID: b84a4680a0d4

Data Scientist III

Indeed · Portland, OR

Mid-level Doctorate

2026-05-23

WA 2026-05-23

Responsibilities

As a Data Scientist III at Indeed, you will leverage your expertise in data science, statistics, AI and machine learning to take on complex product, marketing and business challenges. You will design and implement analytical solutions that guide decisions, optimize product performance or marketing campaigns, and create measurable impact across the organization.
You will work closely with engineering and product or marketing teams to identify opportunities, evaluate initiatives, and develop models and analyses that inform data-driven strategies. You will also contribute to building best practices in data science and mentor others in the team, helping elevate the technical capabilities and impact of those around you.
Oversee the design and execution of advanced analyses, experiments, and machine learning models to address complex questions.
Translate data into actionable insights to guide product, marketing and business decisions.
Develop and maintain scalable, robust data pipelines and models for large-scale product data. Collaborate with engineering and product teams to integrate data science solutions into product workflows.
Mentor and support other data scientists, promoting knowledge sharing and best practices.
Contribute to the development of AI agents and skills, methodologies, and processes that improve the efficiency and impact of the data science team.
Communicate findings clearly through presentations, visualizations, and documentation for diverse audiences.
*Skills/Competencies
Requires a Bachelor's degree in Computer Science, Mathematics, or Statistics, and a minimum of 8 years of related experience; or a Master's degree with a minimum of 6 years of experience; or a PhD with 3 years experience
Expertise in A/B testing and experimentation is required
Solid foundation in data science methods and technologies.
Able to influence technical direction and contribute to long-term planning.
Able to work effectively with other teams and mentor colleagues.
Focused on delivering high-quality, impactful solutions that contribute to business goals.
Excellent written and verbal communication in English, effective with technical and business audiences.

View full posting on CareerOneStop → ID: fb37eb36abff

Data Scientist III

Indeed · Boise, ID

Mid-level Doctorate

2026-05-23

ID 2026-05-23

Responsibilities

As a Data Scientist III at Indeed, you will leverage your expertise in data science, statistics, AI and machine learning to take on complex product, marketing and business challenges. You will design and implement analytical solutions that guide decisions, optimize product performance or marketing campaigns, and create measurable impact across the organization.
You will work closely with engineering and product or marketing teams to identify opportunities, evaluate initiatives, and develop models and analyses that inform data-driven strategies. You will also contribute to building best practices in data science and mentor others in the team, helping elevate the technical capabilities and impact of those around you.
Oversee the design and execution of advanced analyses, experiments, and machine learning models to address complex questions.
Translate data into actionable insights to guide product, marketing and business decisions.
Develop and maintain scalable, robust data pipelines and models for large-scale product data. Collaborate with engineering and product teams to integrate data science solutions into product workflows.
Mentor and support other data scientists, promoting knowledge sharing and best practices.
Contribute to the development of AI agents and skills, methodologies, and processes that improve the efficiency and impact of the data science team.
Communicate findings clearly through presentations, visualizations, and documentation for diverse audiences.
*Skills/Competencies
Requires a Bachelor's degree in Computer Science, Mathematics, or Statistics, and a minimum of 8 years of related experience; or a Master's degree with a minimum of 6 years of experience; or a PhD with 3 years experience
Expertise in A/B testing and experimentation is required
Solid foundation in data science methods and technologies.
Able to influence technical direction and contribute to long-term planning.
Able to work effectively with other teams and mentor colleagues.
Focused on delivering high-quality, impactful solutions that contribute to business goals.
Excellent written and verbal communication in English, effective with technical and business audiences.

View full posting on CareerOneStop → ID: cb8be40266ce

Data Scientist III

Indeed · Helena, MT

Mid-level Doctorate

2026-05-23

MT 2026-05-23

Responsibilities

As a Data Scientist III at Indeed, you will leverage your expertise in data science, statistics, AI and machine learning to take on complex product, marketing and business challenges. You will design and implement analytical solutions that guide decisions, optimize product performance or marketing campaigns, and create measurable impact across the organization.
You will work closely with engineering and product or marketing teams to identify opportunities, evaluate initiatives, and develop models and analyses that inform data-driven strategies. You will also contribute to building best practices in data science and mentor others in the team, helping elevate the technical capabilities and impact of those around you.
Oversee the design and execution of advanced analyses, experiments, and machine learning models to address complex questions.
Translate data into actionable insights to guide product, marketing and business decisions.
Develop and maintain scalable, robust data pipelines and models for large-scale product data. Collaborate with engineering and product teams to integrate data science solutions into product workflows.
Mentor and support other data scientists, promoting knowledge sharing and best practices.
Contribute to the development of AI agents and skills, methodologies, and processes that improve the efficiency and impact of the data science team.
Communicate findings clearly through presentations, visualizations, and documentation for diverse audiences.
*Skills/Competencies
Requires a Bachelor's degree in Computer Science, Mathematics, or Statistics, and a minimum of 8 years of related experience; or a Master's degree with a minimum of 6 years of experience; or a PhD with 3 years experience
Expertise in A/B testing and experimentation is required
Solid foundation in data science methods and technologies.
Able to influence technical direction and contribute to long-term planning.
Able to work effectively with other teams and mentor colleagues.
Focused on delivering high-quality, impactful solutions that contribute to business goals.
Excellent written and verbal communication in English, effective with technical and business audiences.

View full posting on CareerOneStop → ID: 46eaf2e8109e

Data Scientist III - AMZ9442729

AMAZON.COM SERVICES LLC · Seattle, WA

Mid-level Bachelor's

2026-05-23

WA 2026-05-23

Requirements

Bachelor's degree or foreign equivalent degree in Statistics, Applied Mathematics, Economics, Engineering, Computer Science or a related field and two years of experience in the job offered or a related occupation. Employer will accept four years of experience as equivalent to the Bachelor's degree and two years of experience. Must have one year of experience in the following skills: (1) building statistical models and machine learning models using large datasets from multiple resources; (2) building complex data analyses by leveraging scripting languages including Python, Java, or related scripting language; and (3) communicating with users, technical teams, and management to collect requirements, evaluate alternatives, and develop processes and tools to support the organization.

Responsibilities

Own the data science elements of various products to help with data-based decision making, product performance optimization, and product performance tracking. Work directly with product managers to help drive the design of the product. Work with Technical Product Managers to help drive the build planning. Translate business problems and products into data requirements and metrics. Initiate the design, development, and implementation of scientific analysis projects or deliverables. Own the analysis, modelling, system design, and development of data science solutions for products. Write documents and make presentations that explain model/analysis results to the business. Bridge the degree of uncertainty in both problem definition and data scientific solution approaches. Build consensus on data, metrics, and analysis to drive business and system strategy.

View full posting on CareerOneStop → ID: 443c7d8f5701

Data Scientists - Finance

T-Mobile USA, Inc · Bellevue, WA

Mid-level Master's

2026-05-23

WA 2026-05-23

Requirements

(1) Applying statistical and mathematical methodologies including Linear Regression, Logistic Regression, Decision Tree, Cluster Analysis, and Hypothesis Testing to perform segmentation, prediction, forecast, and exploratory analysis;
(2) Extracting, integrating, and processing large-scale structured and unstructured datasets from multiple enterprise data warehouses and transactional databases using advanced SQL, Python and SAS. Performing data integrity checks to ensure completeness and accuracy under SOX compliance framework;
(3) Building and refining financial models to estimate the ASC 820 or IFRS 13 fair value of various assets and liabilities using US GAAP and IFRS compliant approaches by synthesizing data from internal systems, third-party market data, and historical financial performance;
(4) Performing fair value estimates of assets and liabilities using IFRS 13, IFRS 15, ASC460, ASC 606, ASC820, and ASC 805; and
(5) Interpreting and translating the results of statistical and mathematical methodologies including Linear Regression, Logistic Regression, Decision Tree, Cluster Analysis, and Hypothesis Testing and accounting fair value estimates using ASC 460, ASC 606, ASC 820, and ASC 805 prepared by the data scientist into actionable insights for accounting leadership.

Education

PRIMARY REQUIREMENTS: Master's degree in Measurement and Statistics, Applied Statistics, Financial Engineering, or related, and 1 year of relevant work experience.
ALTERNATIVE REQUIREMENTS: Bachelor's degree in Measurement and Statistics, Applied Statistics, Financial Engineering, or related, and 3 years of relevant work experience.
Location: Bellevue, WA
This position is eligible for the employee re

Responsibilities

Operate the model, coordinate with stake holders, and run a process to estimate the liability associated with the Jump Program.
Update the Jump liability program to increase efficiency for various stakeholders.
Provide adhoc analytics on various valuations.
Perform data analytics and statistical analysis to support forecast of device values.
Provide data analytics and statistical analysis to support the estimate of the Apple Forever Liability.
Work with various stakeholders to prepare a model to forecast credit losses on T-Mobile service contracts.
Understand key data architecture and changes to the company to provide insights to various stakeholders with respect to data and valuation estimates.
Telecommuting is permitted, but applicant must work from the worksite location at least 3-4 days per week.
Minimal amount of travel for training or conferences may be required periodically.

View full posting on CareerOneStop → ID: 558f8db1e0a6

AI/ML Engineer - Higher Ed

Cengage Group · Seattle, WA

Mid-level Bachelor's

2026-05-22

WA 2026-05-22

Requirements

Bachelor's degree in Computer Science, Engineering, or related field
4+ years of experience in software engineering, with at least 2 years focused on AI/ML
Strong proficiency in Python with experience building production ML or LLM systems
Hands-on experience with modern AI APIs (OpenAI, Anthropic, AWS Bedrock)
Experience with RAG architectures, vector databases, and embedding models
Solid software engineering fundamentals including testing, CI/CD, and system design
Experience shipping production features at scale (thousands or millions of users)
Strong communication skills to work with product, design, and research partners

Preferred

Experience in EdTech or adjacent domains with production education AI features
Familiarity with agentic AI frameworks (LangChain, LlamaIndex, CrewAI)
Background in learning science, educational psychology, or instructional design
Experience with FERPA compliance and education-industry data handling
Familiarity with accessibility standards (WCAG, Section 508, DOJ accessibility)
Experience with fine-tuning, LoRA, or custom model training
*Tools & Technologies
You should be comfortable with many of the following:
Languages: Python, JavaScript/TypeScript, SQL
AI/ML: OpenAI API, Anthropic API, AWS Bedrock, LangChain, LlamaIndex, Hugging Face
Vector DBs: Pinecone, Weaviate, pgvector, Chroma
Cloud: AWS (Lambda, ECS, SageMaker, Bedrock), Azure OpenAI
Data: Snowflake, Databricks, Postgres, Redis
DevOps: Docker, Terraform, GitHub Actions, CI/CD pipelines
*Key Competencies
Shipping Mindset - delivers features weekly, not quarterly
Technical Craft - writes clean, tested, production-grade code
Learning Orientation - cares about whether AI actually improves learning outcomes
Systems Thinking - sees the full platform and integrates AI cleanly
Collaboration - partners effectively with product, design, research, and platform engineering
Continuous Improvement - iterates on models and features based on data

Responsibilities

*HED AI Feature Development
Ship and improve AI features weekly across Cengage HED platforms
Build and integrate Student Assistant capabilities including tutoring, hinting, and feedback
Develop Instructor Insight Assistant features for course analytics and at-risk student identification
Create Content Studio capabilities for AI-assisted content authoring and adaptation
Integrate LLMs, RAG systems, and agentic workflows into HED platform architectures
*Platform Integration & Engineering
Integrate AI features into existing HED platform architectures and data systems
Partner with platform engineering on API design, scaling, and production deployment
Build retrieval systems against Cengage's proprietary content library (books, assessments, media)
Ensure AI features meet FERPA compliance and accessibility standards (WCAG, DOJ)
Resolve technical blockers and production issues with urgency
*Measurement & Optimization
Monitor feature usage, engagement, and learning outcome impact
Track and improve model performance on quality, cost, and latency dimensions
Partner with learning scientists and researchers on efficacy measurement
Iterate rapidly based on student feedback, instructor feedback, and usage telemetry
Maintain documentation and engineering runbooks for deployed AI features

View full posting on CareerOneStop → ID: de5d6ba5cd8f

Data Scientist

ManpowerGroup · Redmond, WA

Mid-level

2026-05-22

WA 2026-05-22

View full posting on CareerOneStop → ID: b8680b5649b6

Machine Learning Engineer

Zoom · Seattle, WA

Mid-level Master's

2026-05-22

WA 2026-05-22

Responsibilities

Design, implement, and optimize GenAI algorithms, techniques and solutions to address complex
business challenges.
Collaborate with cross-functional teams to integrate research findings into scalable engineering solutions that align with business objectives.
Participate in code reviews, design discussions, and technical presentations to ensure the quality and reliability of our engineering solutions.
Identify opportunities for improvement in existing systems and proposing innovative solutions to enhance performance, scalability, and reliability.
Stay up to date with the newest developments in GenAI research and engineering to continuously improve our technical capabilities.
What we're looking for:
Requires a Bachelor's degree in Computer Science, Computer Engineering, a related field, or a foreign degree equivalent. Must have 3 years of experience in job offered or related occupation. Must have 3 years of experience in the following skills:
Utilizing one or more programming languages such as Python, C, C++, or CUDA in building scalable software systems;
Deep learning frameworks including PyTorch and TensorFlow;
Presenting academic or personal AI projects;
Collaborating with cross-functional teams to present technical concepts to both technical and nontechnical audiences;
Agentic AI including LLM driven AI agents, agentic RAG;
Building scalable, maintainable, and production-ready machine learning systems; and
Analyzing data and troubleshooting issues related to deployed AI systems.
Telecommuting work arrangement permitted one day per week. Four days in office required. Position does not require domestic or international travel.
In Lieu of a Bachelor's degree and 3 years of experience the company will accept the following: Must have Master's degree in Computer Science, Computer Engineering, a related field, or a foreign degree equivalent. Must have 1 years of experience in job offered or related occupation. Must have 1 years of experience in the following skills:

View full posting on CareerOneStop → ID: e5af510de9ba

AI/ML Engineer - Higher Ed

Cengage Group · Portland, OR

Mid-level Bachelor's

2026-05-22

WA 2026-05-22

Requirements

Bachelor's degree in Computer Science, Engineering, or related field
4+ years of experience in software engineering, with at least 2 years focused on AI/ML
Strong proficiency in Python with experience building production ML or LLM systems
Hands-on experience with modern AI APIs (OpenAI, Anthropic, AWS Bedrock)
Experience with RAG architectures, vector databases, and embedding models
Solid software engineering fundamentals including testing, CI/CD, and system design
Experience shipping production features at scale (thousands or millions of users)
Strong communication skills to work with product, design, and research partners

Preferred

Experience in EdTech or adjacent domains with production education AI features
Familiarity with agentic AI frameworks (LangChain, LlamaIndex, CrewAI)
Background in learning science, educational psychology, or instructional design
Experience with FERPA compliance and education-industry data handling
Familiarity with accessibility standards (WCAG, Section 508, DOJ accessibility)
Experience with fine-tuning, LoRA, or custom model training
*Tools & Technologies
You should be comfortable with many of the following:
Languages: Python, JavaScript/TypeScript, SQL
AI/ML: OpenAI API, Anthropic API, AWS Bedrock, LangChain, LlamaIndex, Hugging Face
Vector DBs: Pinecone, Weaviate, pgvector, Chroma
Cloud: AWS (Lambda, ECS, SageMaker, Bedrock), Azure OpenAI
Data: Snowflake, Databricks, Postgres, Redis
DevOps: Docker, Terraform, GitHub Actions, CI/CD pipelines
*Key Competencies
Shipping Mindset - delivers features weekly, not quarterly
Technical Craft - writes clean, tested, production-grade code
Learning Orientation - cares about whether AI actually improves learning outcomes
Systems Thinking - sees the full platform and integrates AI cleanly
Collaboration - partners effectively with product, design, research, and platform engineering
Continuous Improvement - iterates on models and features based on data

Responsibilities

*HED AI Feature Development
Ship and improve AI features weekly across Cengage HED platforms
Build and integrate Student Assistant capabilities including tutoring, hinting, and feedback
Develop Instructor Insight Assistant features for course analytics and at-risk student identification
Create Content Studio capabilities for AI-assisted content authoring and adaptation
Integrate LLMs, RAG systems, and agentic workflows into HED platform architectures
*Platform Integration & Engineering
Integrate AI features into existing HED platform architectures and data systems
Partner with platform engineering on API design, scaling, and production deployment
Build retrieval systems against Cengage's proprietary content library (books, assessments, media)
Ensure AI features meet FERPA compliance and accessibility standards (WCAG, DOJ)
Resolve technical blockers and production issues with urgency
*Measurement & Optimization
Monitor feature usage, engagement, and learning outcome impact
Track and improve model performance on quality, cost, and latency dimensions
Partner with learning scientists and researchers on efficacy measurement
Iterate rapidly based on student feedback, instructor feedback, and usage telemetry
Maintain documentation and engineering runbooks for deployed AI features

View full posting on CareerOneStop → ID: d044f0171ecc

AI/ML Engineer - Higher Ed

Cengage Group · Boise, ID

Mid-level Bachelor's

2026-05-22

ID 2026-05-22

Requirements

Bachelor's degree in Computer Science, Engineering, or related field
4+ years of experience in software engineering, with at least 2 years focused on AI/ML
Strong proficiency in Python with experience building production ML or LLM systems
Hands-on experience with modern AI APIs (OpenAI, Anthropic, AWS Bedrock)
Experience with RAG architectures, vector databases, and embedding models
Solid software engineering fundamentals including testing, CI/CD, and system design
Experience shipping production features at scale (thousands or millions of users)
Strong communication skills to work with product, design, and research partners

Preferred

Experience in EdTech or adjacent domains with production education AI features
Familiarity with agentic AI frameworks (LangChain, LlamaIndex, CrewAI)
Background in learning science, educational psychology, or instructional design
Experience with FERPA compliance and education-industry data handling
Familiarity with accessibility standards (WCAG, Section 508, DOJ accessibility)
Experience with fine-tuning, LoRA, or custom model training
*Tools & Technologies
You should be comfortable with many of the following:
Languages: Python, JavaScript/TypeScript, SQL
AI/ML: OpenAI API, Anthropic API, AWS Bedrock, LangChain, LlamaIndex, Hugging Face
Vector DBs: Pinecone, Weaviate, pgvector, Chroma
Cloud: AWS (Lambda, ECS, SageMaker, Bedrock), Azure OpenAI
Data: Snowflake, Databricks, Postgres, Redis
DevOps: Docker, Terraform, GitHub Actions, CI/CD pipelines
*Key Competencies
Shipping Mindset - delivers features weekly, not quarterly
Technical Craft - writes clean, tested, production-grade code
Learning Orientation - cares about whether AI actually improves learning outcomes
Systems Thinking - sees the full platform and integrates AI cleanly
Collaboration - partners effectively with product, design, research, and platform engineering
Continuous Improvement - iterates on models and features based on data

Responsibilities

*HED AI Feature Development
Ship and improve AI features weekly across Cengage HED platforms
Build and integrate Student Assistant capabilities including tutoring, hinting, and feedback
Develop Instructor Insight Assistant features for course analytics and at-risk student identification
Create Content Studio capabilities for AI-assisted content authoring and adaptation
Integrate LLMs, RAG systems, and agentic workflows into HED platform architectures
*Platform Integration & Engineering
Integrate AI features into existing HED platform architectures and data systems
Partner with platform engineering on API design, scaling, and production deployment
Build retrieval systems against Cengage's proprietary content library (books, assessments, media)
Ensure AI features meet FERPA compliance and accessibility standards (WCAG, DOJ)
Resolve technical blockers and production issues with urgency
*Measurement & Optimization
Monitor feature usage, engagement, and learning outcome impact
Track and improve model performance on quality, cost, and latency dimensions
Partner with learning scientists and researchers on efficacy measurement
Iterate rapidly based on student feedback, instructor feedback, and usage telemetry
Maintain documentation and engineering runbooks for deployed AI features

View full posting on CareerOneStop → ID: 8f1d85c81181

AI/ML Engineer - Higher Ed

Cengage Group · Billings, MT

Mid-level

2026-05-22

MT 2026-05-22

View full posting on CareerOneStop → ID: 7f0adaaeae32

Data Scientist - 3035128

Apex Systems, Inc. · Redmond, WA

Mid-level

2026-05-22

WA 2026-05-22

View full posting on CareerOneStop → ID: b40da831182f

Data Scientists - Finance

T-Mobile USA, Inc. · Bellevue, WA

Mid-level

2026-05-22

WA 2026-05-22

View full posting on CareerOneStop → ID: c52ca62f36b0

Data Scientist

TEKsystems · Seattle, WA

Mid-level

2026-05-21

WA 2026-05-21

Requirements

3-5+ years of data science or analytics experience
Strong SQL and Python skills
Experience with experimentation (A/B testing), hypothesis testing, or causal analysis
Experience working with data pipelines and large-scale datasets
Ability to drive business or product decisions using data

Preferred

Forecasting or time series experience
Product analytics or customer behavior analysis
Experience with cloud or modern data tools (e.g., Snowflake, Databricks)
Exposure to NLP, LLMs, or unstructured data analysis
Technical Skills
Python, SQL, Data Analysis, Experimentation, Predictive Modeling

Responsibilities

Design and analyze experiments (A/B testing) to evaluate product features
Build and maintain data pipelines to support experimentation, analytics, and scalable product insights
Develop predictive models to understand user behavior and system performance
Translate data findings into actionable insights that directly influence product and engineering decisions
Perform analysis using SQL and Python on large datasets
Partner cross-functionally to define metrics and measure impact

View full posting on CareerOneStop → ID: bd47e3f27cd5

Machine Learning Engineer - LLM Evaluation & Automation

TEKsystems · Seattle, WA

Mid-level

2026-05-21

WA 2026-05-21

Requirements

5+ years of experience in ML engineering, NLP, or AI/ML automation
Strong programming skills in Python and SQL
Deep understanding of machine learning concepts with a focus on NLP and advanced LLM capabilities (e.g., Chain-of-Thought, agentic workflows)
Experience working with large-scale datasets and data pipelines
Strong experience with LLM evaluation, prompt engineering, or auto grading systems
Experience developing metrics and KPIs to measure model output quality and consistency

Preferred

Experience with LLM-as-judge systems or human + model evaluation frameworks
Background in inter-rater reliability, evaluation calibration, or judged systems design
Experience with PySpark or distributed data processing tools
Exposure to building dashboards or visualization tools for model performance tracking
Technical Skills
Python, SQL, NLP, LLM Evaluation, Prompt Engineering, Machine Learning, Data Pipelines, Automation Systems
NOTE: This posting is for an existing vacancy. ?
We reserve the right to pay above or below the posted wage based on factors unrelated to sex, race, or any other protected
classification. Eligibility requirements apply to some benefits
and may depend on your job classification and length of employment. Benefits are subject to change and may be subject to specific elections, plan, or program terms. This temporary role may be eligible for the following:
Medical, dental & vision
Insurance (Basic/Supplemental Life & AD&D)

Responsibilities

Design and build LLM-based evaluation frameworks, including automated scoring pipelines and rubric-based grading systems
Build and maintain data pipelines for evaluation datasets using Python, SQL, and scalable processing tools
Translate complex evaluation results into clear, actionable insights for technical and non-technical stakeholders
Implement automation workflows and agentic evaluation systems to improve efficiency and reduce manual efforts
Develop prompt engineering strategies to evaluate output quality, accuracy, and consistency
Create and maintain metrics, KPIs, and dashboards to track and communicate model performance
Conduct error analysis, root-cause investigations, and quality deep dives to guide model improvements
Partner cross-functionally to define evaluation methodologies and integrate them into production workflows

View full posting on CareerOneStop → ID: c794d9571b4c

Data Scientist, Manufacturing Analytics

Ford Motor Company · Olympia, WA

Mid-level Doctorate

2026-05-21

WA 2026-05-21

Responsibilities

Accelerate the application of value-added analytics and machine learning into the portfolio of products for Manufacturing Analytics.
Drive analytic excellence into product teams by collaborating with Data Scientists, Data Engineers and Software Engineers in analytic and machine learning methods.
Work closely with the Product Manager and Product Owner to translate Business Value needs into analytic deliverables and, where appropriate, software products for delivery by product teams.
Work hands-on with the team and other partners to deliver solutions that meet our customer's requirements and needs.
Act as a consultant to the business vs. an order taker.
Balance "doing it right" with "speed to delivery" by identifying and mitigating risk, generating options, educating business and other decision makers, and taking on justified technical debt.
*You'll have...
Bachelor's degree in a quantitative field, such as Data Science, Engineering, Operations Research, Industrial Engineering, Statistics, Mathematics OR Computer Science
2+ year experience hands-on experience with mathematical programming, machine learning, artificial intelligence, optimization/simulation techniques, or statistical analysis
1+ year of experience delivering analytics solutions
1+ year experience with Agile team methodology
Demonstrated technical skills in data analytics, AI/ML, operations research, and/or optimization
*Even better, you may have...
Master's degree or PhD preferred in quantitative field, such as Data Science, Engineering, Operations Research, Industrial Engineering, Statistics, Mathematics, Computer Science, or related field
Knowledge and experience working with OGC and related teams/activities (e.g., Compliance, Litigation and Regulatory)
Proven experience with developing data products/solutions to support analytic applications in Ford's data ecosystem
Experience with Product Driven Operating Model or Agile Product Development Process
Proven proficiency in developing and deploying analytic models, working in a team environment, supporting customers and/or end users
Comfortable working in an environment where problems are not always well-defined
Strong interpersonal and leadership skills, with ability to communicate complex topics to leaders and peers in a simple and clear manne
Well-organized, independent, and ready to work with minimal supervision
Inquisitive, proactive, and interested in learning new tools and techniques
Demonstrated hands on experience with deploying data products and/or analytic models in Ford's on-prem and/or Google Cloud Platform
Demonstrated experience to translate real-world business problems into analytical formulations and interpreting analytics results with non-analytics business partners
Working knowledge of Manufacturing IT legacy systems such as FIS, Maximo, QLS, etc.
Thorough understanding of the 'Common Data Model' standard published by Manufacturing
Understanding of the IIoT Platform architecture including MQTT
You may not check every box, or your experience may look a little different from what we've outlined, but if you think you can bring value to Ford Motor Company, we encourage you to apply!
As an established global company, we offer the benefit of choice. You can choose what your Ford future will look like: will your story span the globe, or keep you close to home? Will your career be a deep dive into what you love, or a series of new teams and new skills? Will you be a leader, a changemaker, a technical expert, a culture builder...or all of the above? No matter what you choose, we offer a work life that works for you, including:
Immediate medical, dental, vision and prescription drug coverage
Flexible family care days, paid parental leave, new parent ramp-up programs, subsidized back-up child care and more
Family building benefits including adoption and surrogacy expense reimbursement, fertility treatments, and more
Vehicle discount program for employees and family members and management leases
Tuition assistance
Established and active employee resource groups
Paid time off for individual and team community service
A generous schedule of paid holidays, including the week between Christmas and New Year's Day
Paid time off and the option to purchase additional vacation time.
This position is a salary grade 5 - salary grade 8 and ranges from $68,300-$192,900.

View full posting on CareerOneStop → ID: aff447194327

Data Scientist, Manufacturing Analytics

Ford Motor Company · Salem, OR

Mid-level Doctorate

2026-05-21

OR 2026-05-21

Responsibilities

Accelerate the application of value-added analytics and machine learning into the portfolio of products for Manufacturing Analytics.
Drive analytic excellence into product teams by collaborating with Data Scientists, Data Engineers and Software Engineers in analytic and machine learning methods.
Work closely with the Product Manager and Product Owner to translate Business Value needs into analytic deliverables and, where appropriate, software products for delivery by product teams.
Work hands-on with the team and other partners to deliver solutions that meet our customer's requirements and needs.
Act as a consultant to the business vs. an order taker.
Balance "doing it right" with "speed to delivery" by identifying and mitigating risk, generating options, educating business and other decision makers, and taking on justified technical debt.
*You'll have...
Bachelor's degree in a quantitative field, such as Data Science, Engineering, Operations Research, Industrial Engineering, Statistics, Mathematics OR Computer Science
2+ year experience hands-on experience with mathematical programming, machine learning, artificial intelligence, optimization/simulation techniques, or statistical analysis
1+ year of experience delivering analytics solutions
1+ year experience with Agile team methodology
Demonstrated technical skills in data analytics, AI/ML, operations research, and/or optimization
*Even better, you may have...
Master's degree or PhD preferred in quantitative field, such as Data Science, Engineering, Operations Research, Industrial Engineering, Statistics, Mathematics, Computer Science, or related field
Knowledge and experience working with OGC and related teams/activities (e.g., Compliance, Litigation and Regulatory)
Proven experience with developing data products/solutions to support analytic applications in Ford's data ecosystem
Experience with Product Driven Operating Model or Agile Product Development Process
Proven proficiency in developing and deploying analytic models, working in a team environment, supporting customers and/or end users
Comfortable working in an environment where problems are not always well-defined
Strong interpersonal and leadership skills, with ability to communicate complex topics to leaders and peers in a simple and clear manne
Well-organized, independent, and ready to work with minimal supervision
Inquisitive, proactive, and interested in learning new tools and techniques
Demonstrated hands on experience with deploying data products and/or analytic models in Ford's on-prem and/or Google Cloud Platform
Demonstrated experience to translate real-world business problems into analytical formulations and interpreting analytics results with non-analytics business partners
Working knowledge of Manufacturing IT legacy systems such as FIS, Maximo, QLS, etc.
Thorough understanding of the 'Common Data Model' standard published by Manufacturing
Understanding of the IIoT Platform architecture including MQTT
You may not check every box, or your experience may look a little different from what we've outlined, but if you think you can bring value to Ford Motor Company, we encourage you to apply!
As an established global company, we offer the benefit of choice. You can choose what your Ford future will look like: will your story span the globe, or keep you close to home? Will your career be a deep dive into what you love, or a series of new teams and new skills? Will you be a leader, a changemaker, a technical expert, a culture builder...or all of the above? No matter what you choose, we offer a work life that works for you, including:
Immediate medical, dental, vision and prescription drug coverage
Flexible family care days, paid parental leave, new parent ramp-up programs, subsidized back-up child care and more
Family building benefits including adoption and surrogacy expense reimbursement, fertility treatments, and more
Vehicle discount program for employees and family members and management leases
Tuition assistance
Established and active employee resource groups
Paid time off for individual and team community service
A generous schedule of paid holidays, including the week between Christmas and New Year's Day
Paid time off and the option to purchase additional vacation time.
This position is a salary grade 5 - salary grade 8 and ranges from $68,300-$192,900.

View full posting on CareerOneStop → ID: bfc28dd922c9

Data Scientist, Manufacturing Analytics

Ford Motor Company · Helena, MT

Mid-level

2026-05-21

MT 2026-05-21

View full posting on CareerOneStop → ID: 6a533828e269

Machine Learning Engineer, Foundation Model Services

Apple · Seattle, WA

Mid-level

2026-05-21

WA 2026-05-21

View full posting on CareerOneStop → ID: 94d3655636d4

Data Scientist , AMXL Worldwide Science

Amazon · Bellevue, WA

Mid-level Doctorate

2026-05-20

WA 2026-05-20

Requirements

Master's degree in Science, Technology, Engineering, or Mathematics (STEM), or experience working in Science, Technology, Engineering, or Mathematics (STEM)
2+ years of data scientist experience
3+ years of data querying languages (e.g. SQL), scripting languages (e.g. Python) or statistical/mathematical software (e.g. R, SAS, Matlab, etc.) experience
3+ years of machine learning/statistical modeling data analysis tools and techniques, and parameters that affect their performance experience
1+ years of guiding and coaching a group of researchers experience
1+ years of working with or evaluating AI systems experience
1+ years of creating or contributing to mathematical textbooks, research papers, or educational content experience
Experience applying theoretical models in an applied environment

Preferred

Ph.D. in Science, Technology, Engineering, or Mathematics (STEM)
Knowledge of machine learning concepts and their application to reasoning and problem-solving
Experience in Python, Perl, or another scripting language
Experience in a ML or data scientist role with a large technology company
Experience in defining and creating benchmarks for assessing GenAI model performance
Experience working on multi-team, cross-disciplinary projects
Experience applying quantitative analysis to solve business problems and making data-driven business decisions
Experience effectively communicating complex concepts through written and verbal communication

Responsibilities

Apply machine learning, statistical modeling, time series analysis, and operations research techniques to build solutions for delivery routing, capacity planning, demand forecasting, workforce scheduling, and network optimization
Analyze large-scale historical and real-time operational data to surface efficiency patterns, bottlenecks, and emerging trends across the AMXL network
Develop, validate, and deploy models that improve cost-to-serve and customer experience
Partner with cross-functional teams to implement data-driven strategies and measure impact
Build scalable, automated pipelines for data ingestion, feature engineering, model training, and validation
Monitor deployed model performance and communicate results through clear reporting on key operational and business metrics

View full posting on CareerOneStop → ID: 22260e66a090

Data Scientist II

Chewy Inc. · Bellevue, WA

Mid-level Master's

2026-05-20

WA 2026-05-20

Requirements

Ability to work with large datasets using distributed computing tools;
Amazon Web Services tools such as Redshift, Snowflake, Google Big Query, SageMaker or other similar platforms;
Object-oriented programming with Python; and
Data visualization tools and packages (Tableau or similar).

View full posting on CareerOneStop → ID: 0ef76487d159

Data Scientist III

Chewy Inc. · Bellevue, WA

Mid-level Doctorate

2026-05-20

WA 2026-05-20

Requirements

At least one data science subject area (e.g., casual inference, LLM's, forecasting, etc.);
Managing the entire data science lifecycle including data prep, exploratory data analysis, modeling, interface with cross functional stakeholders (such as engineering, business, etc.), deploying models to production;
Amazon Web Services tools such as Snowflake;
R, PySpark, Spark, Keras, TensorFlow, Docker, Git version control;
Object-oriented programming with Python;
Data visualization tools and packages (Tableau or similar); and

View full posting on CareerOneStop → ID: 8464227eb95e

Data Scientist III

Chewy Inc. · Bellevue, WA

Mid-level Doctorate

2026-05-20

WA 2026-05-20

Requirements

At least one data science subject area (e.g., casual inference, NLP, forecasting, etc.);
R, PySpark, Spark, Scala, Java, PyTorch, TensorFlow, Docker;
Object-oriented programming with Python; and
Data visualization tools and packages (Tableau or similar).
Managing the entire data science lifecycle including data prep, exploratory data analysis, modeling, interface with engineering;
Amazon Web Services tools such as Redshift, Snowflake, SageMaker or other similar platforms; and

View full posting on CareerOneStop → ID: a50291e8d3d9

Machine Learning Platform Engineer, Apple Services Engineering

Apple · Seattle, WA

Mid-level

2026-05-20

WA 2026-05-20

Requirements

4-8 years of software engineering experience building and shipping production services.
Strong Python. You're fluent with FastAPI, Pydantic, and the modern Python ecosystem. You write code that's clean, tested, and easy for the next person to pick up.
Builder's mindset. You enjoy shipping. You're comfortable iterating quickly on scoped problems and knowing when to slow down for the parts that need it.
Fluency with AI coding tools. You actively use tools like Claude Code (or equivalents) in your day-to-day workflow, including features like skills, slash commands, and agent-style workflows. You have a good intuition for when to lean on them, when to steer them, and how to get high-quality output.
Familiarity with the agentic LLM landscape. You stay current on how modern LLM systems work in production - tool use, MCP servers, agent frameworks, context management, multi-step reasoning. You can hold a real conversation about the tradeoffs.
Hands-on evaluation experience. You've built evaluations for your own agents or LLM systems, or you've worked with evaluation orchestration frameworks like Inspect, Braintrust, LangSmith, Promptfoo, or equivalents (including internal tooling). You understand what makes an evaluation trustworthy vs. theatrical.
Real working knowledge of LLMs in production. You're comfortable with prompt iteration, dataset curation, judge models, and statistical reasoning about non-deterministic outputs. You understand the lifecycle around models even if you haven't trained them yourself.
Solid engineering fundamentals. You understand testing, CI/CD, containerization (Docker), and basic observability. You've shipped services that others depend on and stayed close when they broke.
Clear communicator. You write clear PRs, ask sharp questions, and flag blockers early. You're comfortable disagreeing thoughtfully and changing your mind when the argument is good.
Ownership. When something is broken or unclear, you tend to pick it up rather than wait. You either move it forward or surface it clearly.

Preferred

Experience working on developer platforms, internal tools, or SDKs
Production experience with LLM/agent systems - building, evaluating, or operating them
Familiarity with job orchestration frameworks (Temporal.io, Airflow, or similar)
Distributed compute experience (Ray, Dask, or Kubernetes-based job systems)
Experience with experiment tracking or ML lifecycle tooling (Weights & Biases, MLflow, etc.)
Startup or early-stage experience where you wore multiple hats and shipped under constraint

Responsibilities

We're building the evaluation platform that will serve all of Apple's generative AI and agent systems. Evaluating non-deterministic AI systems is one of the hardest unsolved problems in production ML - and one Apple has to get right at scale. We're building the platform that makes it tractable for every team here.
This is a hands-on engineering role with a lot of autonomy. You'll write a lot of Python and own meaningful pieces of the platform end-to-end. You'll be partnering closely with research engineers, model and serving teams, product and feature teams, and the infra and data platform groups this work integrates with.
Build and ship: Take ownership of features and services within the evaluation platform: APIs, SDKs, orchestration components, evaluation runners. You'll have the room to make calls on your own work and the support to deliver it well.
Productionize ML research: Partner with research engineers to take their prototype code and turn it into reliable services. You'll learn their world quickly and translate research patterns into clean Python that holds up under real load.
Move fast, responsibly: You'll get scoped problems with room to figure out the how. We trust you to balance speed with care, to know when something needs a quick prototype and when it needs a design doc, tests, and a careful rollout.
Improve as you go: Notice the rough edges and pick them up. The flaky test, the slow build, the confusing API, the runbook that's out of date. We want someone who leaves the codebase a little better every week.
Developer experience: Help build the SDKs and abstractions that other Apple teams use to evaluate their models and agents. You'll feel the friction of bad ergonomics directly, which puts you in a great position to fix it.
Operational ownership: Your code runs in production. You write the tests, set up the CI, add the metrics, and stay close when something breaks. You don't need to be an SRE, but you take care of what you ship.

View full posting on CareerOneStop → ID: 152821a80d55

Data Scientist

Capgemini · Seattle, WA

Mid-level

2026-05-19

WA 2026-05-19

Requirements

Design, develop, and deploy AI enabled applications aligned to enterprise needs.
Translate business problems into scalable technical solutions.
Build Generative AI solutions using large language models, including RAG and tool enabled workflows.
Apply AI assisted code generation and developer productivity tools for tasks such as code scaffolding, refactoring, documentation, and test generation.
Design and integrate application components using REST APIs, authentication, error handling, and observability best practices.
Deploy and operate AI solutions in production or production adjacent environments, supporting monitoring and reliability.
The base compensation range for this role in the posted location is $70,000 - $110,000
Contract Type: Permanent
Seattle, WA, US
Brand: Capgemini
Professional Community: Data & AI

Responsibilities

Capgemini is building a Seattle-based AI Cohort to support strategic enterprise engagements focused on Generative AI, intelligent applications, and advanced analytics. This role combines hands-on AI engineering with a delivery and consulting oriented mindset. You will work closely with business and technical stakeholders to shape, build, and scale AI solutions from early exploration through production delivery. Some engagements may follow a Forward Deployment Engineer (FDE)-style working model, where engineers collaborate closely with client teams during solution design and rollout. However, the role remains broad and well suited for candidates who enjoy combining strong technical problem solving with collaborative, client facing delivery. Many initiatives are centered on enterprise cloud and AI platforms, with a strong preference for Azure based architectures and services, as well as modern developer environments that incorporate AI assisted development and code generation tools.

View full posting on CareerOneStop → ID: 9d0a3ff7ef41

Data Scientist

Capgemini · Seattle, WA

Mid-level

2026-05-19

WA 2026-05-19

Requirements

Design, develop, and deploy AI enabled applications aligned to enterprise needs.
Translate business problems into scalable technical solutions.
Build Generative AI solutions using large language models, including RAG and tool enabled workflows.
Apply AI assisted code generation and developer productivity tools for tasks such as code scaffolding, refactoring, documentation, and test generation.
Design and integrate application components using REST APIs, authentication, error handling, and observability best practices.
Deploy and operate AI solutions in production or production adjacent environments, supporting monitoring and reliability.
The base compensation range for this role in the posted location is $70,000 - $110,000
Contract Type: Permanent
Seattle, WA, US
Brand: Capgemini
Professional Community: Data & AI

Responsibilities

Capgemini is building a Seattle-based AI Cohort to support strategic enterprise engagements focused on Generative AI, intelligent applications, and advanced analytics. This role combines hands-on AI engineering with a delivery and consulting oriented mindset. You will work closely with business and technical stakeholders to shape, build, and scale AI solutions from early exploration through production delivery. Some engagements may follow a Forward Deployment Engineer (FDE)-style working model, where engineers collaborate closely with client teams during solution design and rollout. However, the role remains broad and well suited for candidates who enjoy combining strong technical problem solving with collaborative, client facing delivery. Many initiatives are centered on enterprise cloud and AI platforms, with a strong preference for Azure based architectures and services, as well as modern developer environments that incorporate AI assisted development and code generation tools.

View full posting on CareerOneStop → ID: c1e67c313d4d

Machine Learning Engineer, Apple Services Engineering

Apple · Seattle, WA

Mid-level Master's

2026-05-19

WA 2026-05-19

Requirements

Bachelor's degree in Computer Science, Software Engineering, Mathematics, or a related technical field.
7+ years of relevant work experience.
Strong software engineering fundamentals and technical competence in production-quality software development.
Real-world experience with building, scaling, and deploying recommendation systems or large-scale ML models.
Proven grasp of the open-source Python AI/ML tech stack, including PyTorch, scikit-learn, and numpy-scipy-pandas.
Solid understanding of machine learning algorithms, design patterns, and tools, including deep learning and generative AI.
Proficiency with big data technologies, data processing pipelines, and distributed computing (e.g., Spark, Hadoop, Kafka).
Experience with ML infrastructure, model optimization, and serving models at scale with low latency.
Strong written & oral communication skills, with a collaborative mindset.

Preferred

Master's degree in Computer Science, Software Engineering, Mathematics, or a related field; OR equivalent practical industry experience.
Industry experience specifically focused on MLOps, recommendation systems, or search ranking infrastructure.

Responsibilities

Wonder how Apple's Media Products show relevant search results and recommendations across Apple's media offerings - including App Store, Apple TV, Apple Music, Apple Podcasts, and Apple Books? Come join us! Design, build, and deploy machine learning pipelines that personalize the App Store for billions of users worldwide! Prototype, scale, and optimize algorithm improvements. Build robust, large-scale personalized recommender systems for Apps, Games, Videos, Podcasts and Fitness. See your work touch the lives of billions of Apple users worldwide.
The Apple Services Engineering team is one of the most exciting examples of Apple's long-held passion for combining art and technology. We are the people who power the App Store, Apple TV, Apple Music, Apple Podcasts, and Apple Fitness+. And we do it on a massive scale, meeting Apple's high expectations with high performance, to deliver a huge variety of entertainment in over 35 languages to more than 150 countries.
Our scientists and engineers build secure, end-to-end solutions powered by machine learning. Thanks to Apple's unique integration of hardware, software, and services, designers, scientists and engineers here partner to get behind a single unified vision. That vision always includes a deep commitment to strengthening Apple's privacy policy, one of Apple's core values. Although services are a bigger part of Apple's business than ever before, these teams remain small, flexible, and multi-functional, offering greater exposure to the array of opportunities here.
We are looking for an exceptional Machine Learning Engineer to help us build and scale personalization systems using the latest advances in machine learning. With your engineering expertise, we want to develop robust, high-performance solutions to power personalized experiences across the App Store that enrich the lives of our customers. You will have the incredible opportunity to partner with researchers to see cutting-edge AI models deployed reliably at Apple's truly incredible global scale.

View full posting on CareerOneStop → ID: 10a0a4edb19a

AI/ML Engineer - Consultant

Slalom LLC · Seattle, WA

Mid-level

2026-05-18

WA 2026-05-18

Responsibilities

AI/ML Engineer - Consultant
Who You'll Work With
As a modern technology company, Slalom's technologists bring the art of the possible to life for our clients. Our Data + AI capability focuses on delivering next-generation AI and Machine Learning solutions that solve complex business challenges. You'll join a diverse team of engineers, data scientists, and AI thought leaders, working across modern AI platforms and partnering with leading technology providers.
In this role, you will also collaborate closely with business stakeholders and transformation leaders to drive adoption of Generative AI solutions, helping clients translate AI capabilities into real-world impact through coaching, enablement, and change management.
AI/ML Solution Development (Core - ~70%)
Apply Machine Learning, Generative AI, and LLM-based techniques to solve real business problems.
Design, develop, and support delivery of AI/ML solutions (e.g., NLP, recommendation systems, agentic workflows).
Build and deploy AI solutions leveraging modern cloud platforms (AWS, Azure, GCP).
Implement best practices in MLOps / LLMOps, model validation, and production deployment.
Contribute to solution architecture discussions and technical delivery across client engagements.
Stay current on emerging AI/ML trends and contribute to Slalom's AI community through knowledge sharing.
AI Coaching & Adoption (Differentiator - ~30%)
Coach client teams on effective and responsible use of Generative AI tools (e.g., ChatGPT, copilots, custom AI solutions).
Deliver enablement sessions and workshops to drive AI literacy and adoption.
Partner with business stakeholders to identify high-value AI use cases and translate them into technical solutions.
Support organizational change efforts tied to AI adoption, including workflow redesign and user enablement.
Develop reusable assets, playbooks, and best pract

View full posting on CareerOneStop → ID: bed40b2057a2

AI and Machine Learning Assistant Professor/Professional Pra

UTAH STATE UNIVERSITY · Logan, UT

Mid-level Doctorate

2026-05-18

ID 2026-05-18

Requirements

An earned doctorate degree in Electrical Engineering, Computer Engineering, Computer Science, Mathematics, Statistics, or a closely related discipline.
An ability to conduct and disseminate research that applies AI/ML to problems in the electrical engineering domain.
An ability to develop courses in AI/ML and effectively teach undergraduate and graduate level courses in AI/ML and the candidate's specific area of research emphasis in accordance with departmental needs.
An ability to apply for and secure ongoing external funding.
An earned MS degree in Electrical Engineering, Computer Engineering, Computer Science, Mathematics, Statistics, or equivalent work experience.
Strong industrial, commercial, consulting, or research experience in AI/ML systems.
An... For full info follow application link.

Preferred

Preference will be given to candidates with experience building and deploying AI/ML systems.

Responsibilities

Successful candidates for the tenure-track position will be expected to develop an externally funded research program that includes peer-reviewed publications and graduate student mentorship. Both tenure-track and professional practice positions are expected to effectively teach undergraduate and graduate courses, actively participate in assigned department and university duties, and serve their professional society. Ideal candidates will have an interest in developing new courses and degree programs in AI/ML and its applications to engineering.

View full posting on CareerOneStop → ID: a313763fc548

Clinical Data Scientist

Baylor Scott & White Health · Boise, ID

Mid-level

2026-05-16

ID 2026-05-16

View full posting on CareerOneStop → ID: 7754aa13e25a

Clinical Data Scientist

Baylor Scott & White Health · Salem, OR

Mid-level

2026-05-16

OR 2026-05-16

View full posting on CareerOneStop → ID: d7cc39d9e068

Data Scientist , Prime Video - Advertising

Amazon · Seattle, WA

Mid-level

2026-05-15

WA 2026-05-15

Requirements

5+ years of data querying languages (e.g. SQL), scripting languages (e.g. Python) or statistical/mathematical software (e.g. R, SAS, Matlab, etc.) experience
4+ years of data scientist experience
Experience with statistical models e.g. multinomial logistic regression
Experience with statistical methods (e.g., A/B Testing, Regression)

Preferred

2+ years of data visualization using AWS QuickSight, Tableau, R Shiny, etc. experience
Experience managing data pipelines
Experience as a leader and mentor on a data science team

Responsibilities

Use advanced statistical and machine learning techniques to extract insights from large-scale streaming, ad delivery, and auction data sets.
Design and implement end-to-end data science workflows from data acquisition and cleaning through model development, offline evaluation, A/B testing, and production deployment in partnership with product and engineering teams
Build, validate, and maintain the statistical models that support the roadmap including Supply tier classification and Supply Quality Index, ad tolerance and fatigue scoring, and propensity and disengagement prediction
Partner with product and economist teams to design hold out experiments to measure impact of Ad load on revenue and customer engagement; define north star metrics, power calculations, holdout structures, and promotion gates for every major lever.
Support scalable, self-service analytics by building curated datasets for PVa product, ops, sales, and science covering supply, yield, CX, and advertiser diversification outcomes.
Partner with product stakeholders and science peers to identify strategic, data-driven opportunities to improve the customer experience and advertiser results.
Communicate findings, conclusions, and recommendations to technical and non-technical stakeholders
Stay up-to-date on the latest data science tools, techniques, and best practices and help evangelize them across the organization

View full posting on CareerOneStop → ID: 90d212c981a9

Data Scientist, Core Experimentation

OpenAI Inc. · Seattle, WA

Mid-level

2026-05-15

WA 2026-05-15

Responsibilities

We are hiring a Staff-level Data Scientist to help lead the evolution of OpenAI's core experimentation platform. This role is focused on improving the statistical rigor, reliability, and practical usability of experimentation across the company.
You'll work on some of the hardest problems in online experimentation: sample ratio mismatch detection, variance reduction, bias mitigation, metric design, triggered analysis, heterogeneous treatment effects, sequential testing, and experimentation in complex ML systems. You'll also help translate advanced statistical concepts into pragmatic systems and product experiences that teams can actually use.
This is a highly technical individual contributor role with significant influence across methodology, platform architecture, and experimentation best practices. The ideal candidate combines deep statistical expertise with strong systems intuition and hands-on experience building or operating experimentation platforms at scale.
*In this role, you will:
Drive the statistical direction and technical strategy for OpenAI's experimentation platform
Design and improve experimentation methodologies used across product and research teams
Build pragmatic solutions to real-world experimentation challenges, balancing rigor with operational simplicity
Improve the reliability and trustworthiness of experiment results, including detection and prevention of bias, logging issues, and data quality failures
Developscalable analytical systems and pipelines in Python and distributed compute environments
Partner with engineers and product teams to improve experiment design, metric quality, and decision-making practices
Lead investigations into complex experimentation anomalies and measurement failures
Establish best practices for experimentation governance, interpretation, and statistical correctness
Mentor other data scientists and raising the overall technical bar for experimentation and causal inference
*You might thrive in this role if you have:
Experience building, scaling, or operating experimentation platforms at a large technology company
Deep expertise in statistics, causal inference, and online experimentation methodology
Strong understanding of practical experimentation challenges in production systems
Experience with areas such as variance reduction, CUPED, sequential testing, SRM detection, metric design, or heterogeneous effects
Strong coding and systems skills in Python and large-scale data processing frameworks (e.g. Spark)
Experience designing analytical data models and scalable experimentation pipelines
Ability to communicate complex statistical concepts clearly to technical and non-technical audiences
Track record of influencing technical strategy through hands-on technical leadership
Experience in large-scale product experimentation, ML experimentation, ranking system

View full posting on CareerOneStop → ID: e024f1d95905

Language Data Scientist, Alexa International

Amazon · Bellevue, WA

Mid-level Doctorate

2026-05-15

WA 2026-05-15

Requirements

2+ years of data scientist experience
3+ years of data querying languages (e.g. SQL), scripting languages (e.g. Python) or statistical/mathematical software (e.g. R, SAS, Matlab, etc.) experience
3+ years of machine learning/statistical modeling data analysis tools and techniques, and parameters that affect their performance experience
1+ years of guiding and coaching a group of researchers experience
1+ years of working with or evaluating AI systems experience
1+ years of creating or contributing to mathematical textbooks, research papers, or educational content experience
Master's degree or above in Science, Technology, Engineering, or Mathematics (STEM), or experience working in Science, Technology, Engineering, or Mathematics (STEM)
Experience applying theoretical models in an applied environment

Preferred

Ph.D. in Science, Technology, Engineering, or Mathematics (STEM)
Knowledge of machine learning concepts and their application to reasoning and problem-solving
Experience in Python, Perl, or another scripting language
Experience in a ML or data scientist role with a large technology company
Experience in defining and creating benchmarks for assessing GenAI model performance
Experience working on multi-team, cross-disciplinary projects
Experience applying quantitative analysis to solve business problems and making data-driven business decisions
Experience effectively communicating complex concepts through written and verbal communication

Responsibilities

To be successful in this role, you must have a passion for data, efficiency, and accuracy. Specifically, you will:
Own data analyses for customer-facing features, including launch go/no-go metrics for new features and accuracy metrics for existing features
Handle unique data analysis requests from a range of stakeholders, including quantitative and qualitative analyses to elevate customer experience with speech interfaces
Lead and evaluate changing dialog evaluation conventions, test tooling developments, and pilot processes to support expansion to new data areas
Continuously evaluate workflow tools and processes and offer solutions to ensure they are efficient, high quality, and scalable
Provide expert support for a large and growing team of data analysts
Provide support for ongoing and new data collection efforts as a subject matter expert on conventions and use of the data
Conduct research studies to understand speech and customer-Alexa interactions
Collaborate with scientists and product managers, and other stakeholders in defining and validating customer experience metrics

View full posting on CareerOneStop → ID: eaa6ee5d0b4b

Data Scientist (Data Science)

The Boeing Company · Seattle, WA

Mid-level Doctorate

2026-05-14

WA 2026-05-14

Requirements

Familiarity with GPU compute infrastructure and distributed model training.
Familiarity with container technologies (e.g., Docker, Kubernetes).
Shape the direction of generative AI in a mission-critical organization.
Collaborate with a world-class team of engineers, scientists, and domain experts.
Access to cutting-edge infrastructure, models, and research partnerships.
Bachelor's degree in computer science, Machine Learning, Applied Mathematics, Computer Engineering, Software Engineering, Artificial Intelligence, Physics or a closely related field.
3+ years of experience in data science or machine learning.
3+ years of experience in programming in Python and familiarity with data engineering workflows (e.g., Spark, Airflow, SQL).
This position must meet U.S. export control compliance requirements. To meet U.S. export control compliance requirements, a "U.S. Person" as defined by 22 C.F.R. §120.62 is required.
"U.S. Person" includes U.S. Citizen, U.S. National, lawful permanent resident, refugee, or asylee.
*Export Control Details:
US based job, US Person required

Preferred

Master's or PhD in Computer Science, Machine Learning, Applied Mathematics, Computer Engineering, Software Engineering, Artificial Intelligence, Physics or a closely related field
Experience fine-tuning open-source models and integrating APIs from commercial providers.
Experience with deep learning frameworks (e.g., PyTorch, TensorFlow).
Experience in AI ethics and governance in generative models.
Experience with data engineering tools (e.g., SQL, Spark

Education

Education/experience typically acquired through advanced technical education (e.g. Bachelor) and typically 5 or more years' related work experience or an equivalent combination of technical education and experience (e.g. PhD, Master+3 years' related work experience, 9 years' related work experience, etc.).

Responsibilities

At Boeing, we innovate and collaborate to make the world a better place. We're committed to fostering an environment for every teammate that's welcoming, respectful and inclusive, with great opportunity for professional growth. Find your future with us.
*Boeing Defense, Space & Security (BDS) has an exciting opportunity for a Mid-Level Data Scientist - GenAI to join our team located in Seattle, WA or Arlington, VA.
*We are seeking a skilled and innovative Data Scientist to contribute to the development and optimization of advanced AI, Machine Learning (ML), and Generative AI (GenAI) models within BDS. This role offers the opportunity to learn and grow your skills in ML and large language models (LLMs). You will work closely with senior data scientists and cross-functional teams to contribute to AI-driven applications in our organization.
*Successful candidates will have:
Proficiency with deep learning frameworks (e.g., PyTorch, TensorFlow).
Contribute to the development and deployment of models.
Design and implement pipelines for model fine-tuning and evaluation.
Develop prompt engineering strategies and embedding techniques to enhance model performance.
Prototype applications that address specific business needs.
Assist in model performance evaluation and bias/fairness assessments.
Collaborate with MLOps and engineering teams to support model scaling and monitoring.
Share knowledge of AI/ML/GenAI tools and trends with the team and contribute to best practices.
*This position is hybrid. The selected candidate will be required to perform some work onsite at one of the listed location options. This is at the hiring team's discretion and could potentially change in the future.
*This position is for 1st shift.
*This position must meet export control compliance requirements. To meet export control compliance requirements, a "U.S. Person" as defined by 22 C.F.R. §120.15 is required. "U.S. Person" includes U.S. Citizen, lawful permanent resident, refugee, or asylee.

View full posting on CareerOneStop → ID: 7d65307bce22

Data Scientist - Research Informatics

Seattle Children's · Seattle, WA

Mid-level Master's

2026-05-14

WA 2026-05-14

Education

Bachelor's degree or higher in a STEM or relevant analytical field that demonstrates analytical and technical competency and 2+ years as a Data Analyst using data science tools and methods OR a Master's in a STEM or relevant analytical field that demonstrates analytical and technical competency with evidence of work or applied research experience using data science tools and methods.
Experience with statistics as well as machine learning/data mining/etc.
Experience developing and using statistical models and algorithms.
Intermediate or higher experience in least one major data science language (e.g., R, Python).
Experience in use of data visualization tools and methods.
Experience working with source control tools and version management.
Experience in data extraction using at least one data manipulation language/package(e.g., SQL, R-dplyr, SAS DATA step, Python-pandas).
Experience as a member of a delivery team supporting integrated data science products and solutions for a wide range of customer groups.
*Required Credentials

View full posting on CareerOneStop → ID: 2eeab0445572

Data Scientist, Amazon Devices, Devices Sales & Marketing

Amazon · Bellevue, WA

Mid-level Bachelor's

2026-05-14

WA 2026-05-14

Requirements

3+ years of data querying languages (e.g. SQL), scripting languages (e.g. Python) or statistical/mathematical software (e.g. R, SAS, Matlab, etc.) experience
2+ years of data scientist experience
3+ years of machine learning/statistical modeling data analysis tools and techniques, and parameters that affect their performance experience
Bachelor's degree
Experience applying theoretical models in an applied environment

Preferred

Experience in Python, Perl, or another scripting language
Experience in a ML or data scientist role with a large technology company

Responsibilities

The Amazon Devices organization designs, produces and markets Echo Speakers, Kindle e-readers, Fire Tablets, Fire TV Streaming Media Players, Ring and Blink Smart Home & Security products. We are constantly looking to innovate on behalf of customers with new devices in existing or new categories or improving customer experience on existing platforms. The Devices Data Services (DDS) team provides Data Science, Analytics and Engineering support to the broader organization to enable Sales and Marketing activities across all these product lines.
We are looking for an innovative, hands-on and customer-obsessed Data Scientist who can be a strategic partner to the product managers and engineers on the team. Our projects span multiple organizations and require coordination of experimentation, economic and causal analysis, and building predictive machine learning models. A successful candidate will be a problem solver who enjoys diving into data, is excited by difficult modeling challenges, is motivated to build something that will eventually become a production software system, and possesses strong communication skills to effectively interface between technical and business teams.
In this role, you will be a technical expert with massive impact. You will take the lead on developing
advanced ML systems that are key to reaching our customers with the right recommendations at the right time. Your work will directly impact the success of Amazon's growing Devices business. You will work across diverse science/engineering/business teams. You will work on critical data science problems, building high quality, reliable, accurate, and consistent code sets that are aligned with our business needs.
Key Performance Areas
Implement statistical or machine learning methods to solve specific business problems.
Improve upon existing methodologies by developing new data sources, testing model enhancements, and fine-tuning model parameters.
Directly contribute to development of modern automated recommendation systems
Build customer-facing reporting tools to provide insights and metrics to track model performance and explain variance
Collaborate with researchers, software developers, and business leaders to define product requirements, provide analytical support, and communicate feedback
You will work with other scientists, engineers, product managers, and marketers to develop new products that benefit our customers and help us reach our business goals. You will own solutions from end to end: conceptualization, prioritization, development, delivery, and productionalization.

View full posting on CareerOneStop → ID: 505a54140149

Machine Learning - Compiler Engineer II, Annapurna Labs

Amazon · Seattle, WA

Mid-level Doctorate

2026-05-14

WA 2026-05-14

Requirements

3+ years of non-internship professional software development experience
2+ years of non-internship design or architecture (design patterns, reliability and scaling) of new and existing systems experience
Experience programming with at least one software programming language
3+ years of non-internship professional software development, or 3+ years of software development experience
2+ years of experience architecting and optimizing compilers
Proficiency with 1 or more of the following programming languages: C++ (preferred), C, Python

Preferred

3+ years of full software development life cycle, including coding standards, code reviews, source control management, build processes, testing, and operations experience
Bachelor's degree in computer science or equivalent
PhD in computer science, computer engineering, or related field, or MS degree
Experience with multiple toolchains and Instruction Set Architectures
Proficiency with resource management, scheduling, code generation, and compute graph optimization
Experience optimizing Tensorflow, PyTorch or MxNET deep learning models

View full posting on CareerOneStop → ID: a724fa94a580

Machine Learning Engineer, Ad Response Prediction

Amazon · Seattle, WA

Mid-level Bachelor's

2026-05-14

WA 2026-05-14

Requirements

3+ years of non-internship professional software development experience
3+ years of full software development life cycle, including coding standards, code reviews, source control management, build processes, testing, and operations experience
2+ years of designing and developing large-scale, multi-tiered, multi-threaded, embedded or distributed software applications, tools, systems, and services using: C#, C++, Java, or Perl experience
Knowledge of machine learning model architecture and inference

Preferred

Knowledge of Machine Learning and LLM fundamentals, including transformer architecture, training/inference lifecycles, and optimization techniques
Knowledge of ML frameworks including JAX, PyTorch, vLLM, SGLang, Dynamo, TorchXLA, and TensorRT
1+ years of building large-scale machine-learning infrastructure for online recommendation, ads ranking, personalization or search experience
Bachelor's degree in Computer Science, Engineering, Mathematics, or a related field
Experience developing, deploying and managing AI products at scale

Responsibilities

Own technical vision and direction - Identify problems, develop solutions, and embrace performance metrics to assess system health
Build and grow your team - Wear many hats (software design, implementation, project management, operations, business partnerships) and grow leaders within your group
Collaborate on product direction - Build strong relationships across engineering, Product, UX, and QA to deliver the right product for customers
Lead beyond your team - Contribute to a growing community of engineering leaders, sharing experience and technical acumen to drive org-wide technology decisions
Own your own shop - Our products reach hundreds of millions of customers globally; services must meet high standards for operational excellence (24x7x365)
Highly analytical - You solve problems backed by verifiable data, driving processes, tools, and statistical methods that support rational decision-making
Team obsessed - You grow team members, foster creative atmospheres for innovation, and hold engineers accountable for smart decisions and results
Humbitious - Ambitious yet humble; you use introspection and feedback to continuously raise the ba
Engaged by ambiguity - You explore new problem spaces with unique constraints and non-obvious solutions, quickly identifying gaps and the right people to fill them

View full posting on CareerOneStop → ID: 2a7c3a205fdf

Machine Learning Engineer II, Pricing

Uber · Seattle, WA

Mid-level Doctorate

2026-05-13

WA 2026-05-13

Requirements

Ph.D., M.S. or Bachelor's degree in Computer Science, Machine Learning, or Operations Research, or equivalent technical background with exceptional demonstrated impact
2+ years of experience in developing and deploying machine learning models and optimization algorithms in large-scale production environments
Proficiency in programming languages such as Python, Scala, Java, or Go
Experience with large-scale data systems (e.g. Spark, Ray), real-time processing (e.g. Flink), and microservices architectures
Experience in the development, training, productionization and monitoring of ML solutions at scale, ranging from offline pipelines to online serving and MLOps
Familiarity with modern ML algorithms (e.g. DNNs, multi-task models, transformers) and mathematical optimization (e.g. LP, convex optimization), combined with proven ability and ambition to continuously deepen expertise in these areas

Preferred

Experience in translating ambiguous business problems into technical solutions in a structured and principled way
Strong communication skills, including through documentation and design discussions
Experience in developing and deploying pricing algorithms for multi-sided real-time marketplaces with strategic agent behavio
Experience in reinforcement learning and causal machine learning
For New York, NY-based roles: The base salary range for this role is USD$171,000 per year - USD$190,000 per year. For San Francisco, CA-based roles: The base salary range for this role is USD$171,000 per year - USD$190,000 per year. For Seattle, WA-based roles: The base salary range for this role is USD$171,000 per year - USD$190,000 per year. For Sunnyvale, CA-based roles: The base salary range for this role is USD$171,000 per year - USD$190,000 per year. For all US locations, you will be eligible to participate in Uber's bonus program, and may be offered an equity award & other types of comp. All full-time employees are eligible to participate in a 401(k) plan. You will also be eligible for various benefits. More details can be found at the following link https://jobs.uber.com/en/benefits.

Responsibilities

Uber's Marketplace is at the heart of Uber's business and the Dynamic Supply Pricing (DSP) team develops the models, algorithms, signals, and large-scale distributed systems that power real-time driver pricing for billions of rides. Engineers on the team work on cutting-edge marketplace ML problems and real-time multi-objective optimizations serving 1M+ predictions/second. They regularly present $1B+ opportunities to executive stakeholders and receive close mentorship from the most senior engineers within the organization, setting you up for fast-tracked career growth and the opportunity to learn from experienced technical leaders.
We are looking for exceptional ML engineers with a track record of extraordinary impact and with a passion for building large-scale systems that optimize multi-sided real-time marketplaces. In this role, you will lead the design, development, and productionization of advanced ML models and pricing algorithms, covering deep learning, causal modeling, and reinforcement learning. You will work with engineers, product managers, and scientists to set the team's technical direction and solve some of Uber's most challenging and most complex business problems in order to provide earnings opportunities for millions of drivers worldwide.
*What You Will Do
Design, develop, and productionize end-to-end ML solutions for large-scale distributed systems serving billions of trips
Develop novel pricing approaches for online marketplaces combining machine learning, algorithmic game theory, and optimization to provide earnings opportunities for millions of drivers
Partner with senior engineers to plan the scope and execution of projects and mentor junior team members on design and implementation
Work with a team of engineers, product managers, and scientists to design and deliver high-impact technical solutions to complex business problems

View full posting on CareerOneStop → ID: c8b958526340

Machine Learning Engineer, Ad Response Prediction

Amazon · Seattle, WA

Mid-level Bachelor's

2026-05-13

WA 2026-05-13

Requirements

3+ years of non-internship professional software development experience
3+ years of full software development life cycle, including coding standards, code reviews, source control management, build processes, testing, and operations experience
2+ years of designing and developing large-scale, multi-tiered, multi-threaded, embedded or distributed software applications, tools, systems, and services using: C#, C++, Java, or Perl experience
Knowledge of machine learning model architecture and inference

Preferred

Knowledge of Machine Learning and LLM fundamentals, including transformer architecture, training/inference lifecycles, and optimization techniques
Knowledge of ML frameworks including JAX, PyTorch, vLLM, SGLang, Dynamo, TorchXLA, and TensorRT
1+ years of building large-scale machine-learning infrastructure for online recommendation, ads ranking, personalization or search experience
Bachelor's degree in Computer Science, Engineering, Mathematics, or a related field
Experience developing, deploying and managing AI products at scale

Responsibilities

Own technical vision and direction - Identify problems, develop solutions, and embrace performance metrics to assess system health
Build and grow your team - Wear many hats (software design, implementation, project management, operations, business partnerships) and grow leaders within your group
Collaborate on product direction - Build strong relationships across engineering, Product, UX, and QA to deliver the right product for customers
Lead beyond your team - Contribute to a growing community of engineering leaders, sharing experience and technical acumen to drive org-wide technology decisions
Own your own shop - Our products reach hundreds of millions of customers globally; services must meet high standards for operational excellence (24x7x365)
Highly analytical - You solve problems backed by verifiable data, driving processes, tools, and statistical methods that support rational decision-making
Team obsessed - You grow team members, foster creative atmospheres for innovation, and hold engineers accountable for smart decisions and results
Humbitious - Ambitious yet humble; you use introspection and feedback to continuously raise the ba
Engaged by ambiguity - You explore new problem spaces with unique constraints and non-obvious solutions, quickly identifying gaps and the right people to fill them

View full posting on CareerOneStop → ID: 10037c1d3b1f

Applied ML Engineer

Paramount · Los Angeles, CA

Mid-level

2026-05-13

WA 2026-05-13

View full posting on CareerOneStop → ID: c7cc828cb229

Machine Learning Engineer - Health AIML

Apple · Cupertino, CA

Mid-level

2026-05-13

WA 2026-05-13

View full posting on CareerOneStop → ID: 51d5516404f4

Machine Learning Engineer II

Uber · Sunnyvale, CA

Mid-level

2026-05-13

WA 2026-05-13

View full posting on CareerOneStop → ID: 6446de86e86f

Machine Learning Engineer II

Uber · San Francisco, CA

Mid-level

2026-05-13

WA 2026-05-13

View full posting on CareerOneStop → ID: 4ce93513e961

Machine Learning Engineer II, Pricing

Uber · San Francisco, CA

Mid-level

2026-05-13

WA 2026-05-13

View full posting on CareerOneStop → ID: 442bb6ccad18

Machine Learning Engineer II, Pricing

Uber · Sunnyvale, CA

Mid-level

2026-05-13

WA 2026-05-13

View full posting on CareerOneStop → ID: abaa0f16b962

Data Scientist - INTL India - 99c1e7e0

Insight Global · Tempe, AZ

Mid-level

2026-05-13

AZ 2026-05-13

View full posting on CareerOneStop → ID: 4ded0839ae54

Data Scientist

Love's Travel Stops & Country Stores · Oklahoma City, OK

Mid-level

2026-05-13

OK 2026-05-13

View full posting on CareerOneStop → ID: a0ed38aa9f84

Statistician/Data Scientist - Data Insights and Decision Support

General Motors · Austin, TX

Mid-level

2026-05-13

TX 2026-05-13

View full posting on CareerOneStop → ID: 14107aa16331

Data Scientist III

RELX INC · Minneapolis, MN

Mid-level

2026-05-13

MN 2026-05-13

View full posting on CareerOneStop → ID: fcb67947d859

Data Scientist III

RELX INC · Saint Paul, MN

Mid-level

2026-05-13

MN 2026-05-13

View full posting on CareerOneStop → ID: f34990984678

Data Scientist (MMM)

FocusKPI Inc. · Bentonville, AR

Mid-level

2026-05-13

AR 2026-05-13

View full posting on CareerOneStop → ID: 3462518d1941

Data Scientist

SAIC · Huntsville, AL

Mid-level

2026-05-13

AL 2026-05-13

View full posting on CareerOneStop → ID: 2f30bf7fcbe0

Data Scientist II - Fraud Reporting

Truist · Charlotte, NC

Mid-level

2026-05-13

NC 2026-05-13

View full posting on CareerOneStop → ID: a0203ef47865

Data Scientist II

F5, Inc. · Seattle, WA

Mid-level

2026-05-13

WA 2026-05-13

View full posting on CareerOneStop → ID: fdcd8c81601b

Data Scientist/Statistician

Intel · Hillsboro, OR

Mid-level Doctorate

2026-05-12

WA 2026-05-12

Requirements

You must possess the minimum qualifications to be initially considered for this position. Preferred qualifications are in addition to the minimum requirements and are considered a plus factor in identifying top candidates.
Master's or PhD degree in Statistics, Data Science or Industrial Engineering.
4+ years working in statistics or data science
2+ years working on quality systems such as process control systems and change control systems
1+ year working on PowerBI or similar dashboards
1+ years in data analytics and machine learning (Python, R, JMP, etc.) and relational databases (SQL).

Preferred

1+ years working on fault detection systems
2+ years in a Technical leadership role.
3+ months working knowledge with any of following technologies: JSL, Python, Spark, NiFi, Hadoop, HBase, S3 object storage, Kubernetes, REST APIs and services.
3+ months working knowledge with CI/CD (Continuous Integration/Continuous Deployment) and proficiency with GitHub and GitHub Actions.
Prior interaction with factory automation systems
Requirements listed would be obtained through a combination of industry relevant job experience, internship experiences and or schoolwork/classes/research.

Responsibilities

Intel Foundry Statistics and Data Science team's mission is to drive statistically sound methodologies into business practices and systems to help organization manage change control decisions, monitor capability of the process, ensure matching across tools and fabs, and drive best in class process control systems. Our team reports into the foundry quality and reliability team and is essential for driving transformation of Intel to be focused on not just process development, but a great partner for our foundry customers to help turn data into information. Our team is looking for an engineer with background in statistics and data science with strong technical skills in applied statistics, good communication skills, ability to also help support and develop modern AI/ML solutions.
As a Statistician and Data Scientist in the TD AI office, you will partner with Intel's factory automation organization and Foundry TD's functional areas to support semiconductor process development and transfer of these systems to worldwide virtual factory network.
The primary responsibilities for this role will include, but are not limited to:
Ensuring organization leverages appropriate data and analyses to make change control decisions
Drives organization to use process control systems to improve capability, matching, and stability of semiconductor process technologies
Use predictive modeling, statistics, Machine Learning, Data Mining, and other data analysis techniques to collect, explore, and extract insights from the structure and unstructured data.
Develop software, algorithms and applications to apply mathematics to data, perform large scale experimentation and build data driven apps to translate data into intelligence, solve a variety of business problems and enable business strategy.
Assist the business with casual inferences; observations with finding patterns and relationships in data.
Interfacing with process and integration functional area analytics teams to help solve problems
A successful candidate will have proven experience demonstrating the following skills and behavioral traits:
Experience in using AI/ML/Analytics algorithms and methodologies
Developing statistical methodologies
Ability to code statistical analysis, data cleaning, and data manipulation via common languages such as JSL, Python, and SQL
Understanding of data structures
Strong written and oral communication skills.
Ability to train others
Analytical problem solving and troubleshooting skills.
Teamwork skills and partnership skills.
High tolerance of ambiguity.
High level of self-motivation

View full posting on CareerOneStop → ID: 8ef4c4eed089

AI/ML Engineer (Hybrid)

Cisco · San Jose, CA

Mid-level

2026-05-12

WA 2026-05-12

View full posting on CareerOneStop → ID: 15100ec5664b

Camera Machine Learning Engineer - Camera Hardware

Apple · San Francisco, CA

Mid-level

2026-05-12

WA 2026-05-12

View full posting on CareerOneStop → ID: 195019923c17

Machine Learning Engineer

SAP · Palo Alto, CA

Mid-level

2026-05-12

CA 2026-05-12

View full posting on CareerOneStop → ID: bbddf971feee

Photonic Engineer, Machine Learning Systems, Platforms

Google · Sunnyvale, CA

Mid-level

2026-05-12

CA 2026-05-12

View full posting on CareerOneStop → ID: 01485d4f393e

Product Data Scientist, Insights, Analytics, Platforms and Devices

Google · Mountain View, CA

Mid-level

2026-05-12

CA 2026-05-12

View full posting on CareerOneStop → ID: 5fc1c648a787

Software Engineer, Machine Learning

Google · Mountain View, CA

Mid-level

2026-05-12

CA 2026-05-12

View full posting on CareerOneStop → ID: 289b04d02b5a

Software Engineer, Machine Learning Platform (Tapestry)

Google · Mountain View, CA

Mid-level

2026-05-12

CA 2026-05-12

View full posting on CareerOneStop → ID: 49ba8d652772

Data Scientist/Statistician

Intel · Phoenix, AZ

Mid-level

2026-05-12

AZ 2026-05-12

View full posting on CareerOneStop → ID: eb9bf3fa68e5

Data Scientist

Uniti · Little Rock, AR

Mid-level

2026-05-12

AR 2026-05-12

View full posting on CareerOneStop → ID: 6a27e6a97290

Data Scientist- #26-10985

US Tech Solutions · Chattanooga, TN

Mid-level

2026-05-12

TN 2026-05-12

View full posting on CareerOneStop → ID: d1af4ea90111

Data Scientist II, Amazon Stores Security

Amazon · Seattle, WA

Mid-level Doctorate

2026-05-10

WA 2026-05-10

Requirements

2+ years of data scientist experience
3+ years of data querying languages (e.g. SQL), scripting languages (e.g. Python) or statistical/mathematical software (e.g. R, SAS, Matlab, etc.) experience
3+ years of machine learning/statistical modeling data analysis tools and techniques, and parameters that affect their performance experience

Preferred

Ph.D. in Science, Technology, Engineering, or Mathematics (STEM)
Experience in Python, Perl, or another scripting language
Experience effectively communicating complex concepts through written and verbal communication

Responsibilities

Demonstrate thorough technical knowledge on feature engineering of massive datasets, effective exploratory data analysis, and model building using industry standard AI/ML models and working with Large Language Models
With your broad expertise in a variety of data science disciplines, recommend the right data science strategy and drive solution to complex or ambiguous problems
Work closely with internal stakeholders like the business teams, engineering teams and partner teams, influence their strategies to align with your focus area
Innovate by adapting new modeling techniques and procedures
Passionate about working with huge data sets ( training/fine tuning) and be someone who loves to bring datasets together to answer business questions. You should have deep expertise in creation and management of datasets
Exposure at implementing and operating stable, scalable data flow solutions from production systems into end-user facing applications/reports. These solutions will be fault tolerant, self-healing and adaptive.
Show good judgment when making trade-offs between short-term customer, market, or research needs and long-term operations or technology needs.

View full posting on CareerOneStop → ID: 6ae2fbb77b15

Data Scientist II, Long Term Planning and Forecasting

Amazon · Bellevue, WA

Mid-level Doctorate

2026-05-10

WA 2026-05-10

Requirements

2+ years of data scientist experience
3+ years of data querying languages (e.g. SQL), scripting languages (e.g. Python) or statistical/mathematical software (e.g. R, SAS, Matlab, etc.) experience
3+ years of machine learning/statistical modeling data analysis tools and techniques, and parameters that affect their performance experience
1+ years of guiding and coaching a group of researchers experience
1+ years of working with or evaluating AI systems experience
1+ years of creating or contributing to mathematical textbooks, research papers, or educational content experience
Master's degree in Science, Technology, Engineering, or Mathematics (STEM), or experience working in Science, Technology, Engineering, or Mathematics (STEM)
Experience applying theoretical models in an applied environment

Preferred

Ph.D. in Science, Technology, Engineering, or Mathematics (STEM)
Knowledge of machine learning concepts and their application to reasoning and problem-solving
Experience in Python, Perl, or another scripting language
Experience in defining and creating benchmarks for assessing GenAI model performance
Experience effectively communicating complex concepts through written and verbal communication
Experience in forecasting analyses

Responsibilities

As a Data Scientist in LTPF (Long-Term Planning & Forecasting):
You will develop causal inference models, automated explainability frameworks, and variance bridging methodologies that translate LTPF's forecasts and plans into actionable business intelligence.
Your work will enable leadership to understand why forecasts and actuals diverge, what is driving demand shifts, and how strategic decisions propagate through the planning ecosystem.
You will build automated Plan-vs-Actual and Actual-vs-Actual variance decomposition models that quantify the contribution of individual demand drivers to observed gaps across revenue, price, units, inventory, and capacity metrics at multiple granularities to serve audiences from working-level analysts to VP-level planning reviews cycles.
You will build and maintain a causal model library with standardized hypothesis generation and validation pipelines, applying techniques from causal inference, time-series econometrics, and Bayesian methods. Each model will include calibrated confidence scoring and reusable components that scale across worldwide marketplaces.
You will develop GenAI-powered narrative generation capabilities that synthesize quantitative variance outputs into human-readable performance summaries and design automated hypothesis ranking to determine which demand drivers are most responsible for observed forecast error.
Amazon offers a full range of benefits that support you and eligible family members, including domestic partners and their children. Benefits can vary by location, the number of regularly scheduled hours you work, length of employment, and job status such as seasonal or temporary employment.
The benefits that generally apply to regular, full-time employees include:
Medical, Dental, and Vision Coverage
Maternity and Parental Leave Options
Paid Time Off (PTO)
If you are not sure that every qualification on the list above describes you exactly, we'd still love to hear from you!
At Amazon, we value people with unique backgrounds, experiences, and skillsets. If you're passionate about this role and want to make an impact on a global scale, please apply!

View full posting on CareerOneStop → ID: 39530c4e672c

Data Scientist II, Long Term Planning and Forecasting

Amazon · Bellevue, WA

Mid-level Doctorate

2026-05-10

WA 2026-05-10

Requirements

2+ years of data scientist experience
3+ years of data querying languages (e.g. SQL), scripting languages (e.g. Python) or statistical/mathematical software (e.g. R, SAS, Matlab, etc.) experience
3+ years of machine learning/statistical modeling data analysis tools and techniques, and parameters that affect their performance experience
1+ years of guiding and coaching a group of researchers experience
1+ years of working with or evaluating AI systems experience
1+ years of creating or contributing to mathematical textbooks, research papers, or educational content experience
Master's degree in Science, Technology, Engineering, or Mathematics (STEM), or experience working in Science, Technology, Engineering, or Mathematics (STEM)
Experience applying theoretical models in an applied environment

Preferred

Ph.D. in Science, Technology, Engineering, or Mathematics (STEM)
Knowledge of machine learning concepts and their application to reasoning and problem-solving
Experience in Python, Perl, or another scripting language
Experience in defining and creating benchmarks for assessing GenAI model performance
Experience effectively communicating complex concepts through written and verbal communication

Responsibilities

As a Data Scientist in LTPF (Long-Term Planning & Forecasting):
You will develop causal inference models, automated explainability frameworks, and variance bridging methodologies that translate LTPF's forecasts and plans into actionable business intelligence.
Your work will enable leadership to understand why forecasts and actuals diverge, what is driving demand shifts, and how strategic decisions propagate through the planning ecosystem.
You will build automated Plan-vs-Actual and Actual-vs-Actual variance decomposition models that quantify the contribution of individual demand drivers to observed gaps across revenue, price, units, inventory, and capacity metrics at multiple granularities to serve audiences from working-level analysts to VP-level planning reviews cycles.
You will build and maintain a causal model library with standardized hypothesis generation and validation pipelines, applying techniques from causal inference, time-series econometrics, and Bayesian methods. Each model will include calibrated confidence scoring and reusable components that scale across worldwide marketplaces.
You will develop GenAI-powered narrative generation capabilities that synthesize quantitative variance outputs into human-readable performance summaries and design automated hypothesis ranking to determine which demand drivers are most responsible for observed forecast error.
Amazon offers a full range of benefits that support you and eligible family members, including domestic partners and their children. Benefits can vary by location, the number of regularly scheduled hours you work, length of employment, and job status such as seasonal or temporary employment.
The benefits that generally apply to regular, full-time employees include:
Medical, Dental, and Vision Coverage
Maternity and Parental Leave Options
Paid Time Off (PTO)
If you are not sure that every qualification on the list above describes you exactly, we'd still love to hear from you!
At Amazon, we value people with unique backgrounds, experiences, and skillsets. If you're passionate about this role and want to make an impact on a global scale, please apply!

View full posting on CareerOneStop → ID: 5953602d6eef

AI and ML Engineer

SAIC · San Diego, CA

Mid-level

2026-05-10

CA 2026-05-10

View full posting on CareerOneStop → ID: 37eac646aaa4

Data Scientist - Predictive/AI-Driven Analytics

Insight Global · Burlingame, CA

Mid-level

2026-05-10

CA 2026-05-10

View full posting on CareerOneStop → ID: 24f89261a0f2

Data Scientists/Business Intelligence Analyst

Talent Clustr LLC · Longmont, CO

Mid-level

2026-05-10

CO 2026-05-10

View full posting on CareerOneStop → ID: 22290aff1cc9

Software Development Engineer, Measurement, Ad Tech, and Data Science (MADS) Foundations- Traffic

Amazon · Seattle, WA

Mid-level Bachelor's

2026-05-09

WA 2026-05-09

Requirements

Expertise in large-scale distributed data processing (Spark, EMR, or equivalent)
Demonstrated ownership of end-to-end system architecture on complex, cross-team projects
Ability to influence technical decisions across organizational boundaries without direct authority
Experience operating production systems under strict SLAs at massive scale
3+ years of non-internship professional software development experience
2+ years of non-internship design or architecture (design patterns, reliability and scaling) of new and existing systems experience
1+ years of designing and developing large-scale, multi-tiered, multi-threaded, embedded or distributed software applications, tools, systems, and services using: C#, C++, Java, or Perl experience
1+ years of Object Oriented Design experience
Experience programming with at least one software programming language

Preferred

3+ years of full software development life cycle, including coding standards, code reviews, source control management, build processes, testing, and operations experience
Bachelor's degree in computer science or equivalent

Responsibilities

As a SDE , you will:
Own team architecture and lead design on multi-engineer efforts across our Spark-based EMR pipelines, decoration jobs, and publication systems
Navigate ambiguous technical problems with conflicting constraints - regulatory deadlines, performance requirements, cost targets, and cross-org dependencies
Identify one-way-door decisions, proactively address architectural deficiencies, and ensure Traffic's design doesn't limit what downstream teams can build
Drive adoption of engineering best practices and maintain sound operations - alarms, telemetry, runbooks - for a system with tier-1 SLAs
Mentor engineers, contribute to recruiting, and lead constructive technical dialog within the team and across Ads, Customer Trust, and identity-owning upstream systems
On a typical day as an Ads Traffic SDE, you might:
Start your morning with a team stand-up to align on priorities and address any blockers
Collaborate with product managers to refine requirements for upcoming features
Write code and develop solutions for complex technical challenges
Review pull requests from team members, providing constructive feedback
Participate in design discussions for new services or features
Debug and troubleshoot production issues as they arise
Attend learning sessions to stay current with Ads technologies
Document your work and contribute to technical specifications
Engage with customers or internal stakeholders to better understand their needs

View full posting on CareerOneStop → ID: b5b20b65377f

Data Scientist

Zoom · San Jose, CA

Mid-level

2026-05-09

CA 2026-05-09

View full posting on CareerOneStop → ID: 4b47557e12b0

Data Scientist III - AMZ9803634

Amazon · San Diego, CA

Mid-level

2026-05-09

CA 2026-05-09

View full posting on CareerOneStop → ID: 9da6a32e1597

Machine Learning Engineer - Agentic AI

Apple · Sunnyvale, CA

Mid-level

2026-05-09

CA 2026-05-09

View full posting on CareerOneStop → ID: 0ec92f4171ae

Machine Learning Engineering - Intelligent Foundations and Experiences (IFX)

Capital One · Plano, TX

Mid-level

2026-05-09

TX 2026-05-09

View full posting on CareerOneStop → ID: c316424c03f4

Data Scientist Specialist

3M · Maplewood, MN

Mid-level

2026-05-09

MN 2026-05-09

View full posting on CareerOneStop → ID: ebcf2986c683

Protein Design Data Scientist Postdoc

Bayer · Chesterfield, MO

Mid-level

2026-05-09

MO 2026-05-09

View full posting on CareerOneStop → ID: 0fad867a01b1

AI/ML Engineer - Remote

UnitedHealth Group · Schaumburg, IL

Mid-level

2026-05-09

IL 2026-05-09

View full posting on CareerOneStop → ID: eb982f95098f

Data Scientist

Actalent · Birmingham, AL

Mid-level

2026-05-09

AL 2026-05-09

View full posting on CareerOneStop → ID: 5c2b31583b30

Machine Learning Detection Engineer (Remote, East/Central)

CrowdStrike, Inc. · Frankfort, KY

Mid-level

2026-05-09

KY 2026-05-09

View full posting on CareerOneStop → ID: b317294f6436

Data Scientist, Advertising, AMPI Measurement

Amazon · Seattle, WA

Mid-level

2026-05-09

WA 2026-05-09

View full posting on CareerOneStop → ID: caf75b34e747

Data Scientist, WW Ops FP&A

Amazon · Bellevue, WA

Mid-level Doctorate

2026-05-08

WA 2026-05-08

Requirements

2+ years of data scientist experience
3+ years of data querying languages (e.g. SQL), scripting languages (e.g. Python) or statistical/mathematical software (e.g. R, SAS, Matlab, etc.) experience
3+ years of machine learning/statistical modeling data analysis tools and techniques, and parameters that affect their performance experience
1+ years of guiding and coaching a group of researchers experience
1+ years of working with or evaluating AI systems experience
1+ years of creating or contributing to mathematical textbooks, research papers, or educational content experience
Master's degree in Science, Technology, Engineering, or Mathematics (STEM), or experience working in Science, Technology, Engineering, or Mathematics (STEM)
Experience applying theoretical models in an applied environment

Preferred

Ph.D. in Science, Technology, Engineering, or Mathematics (STEM)
Knowledge of machine learning concepts and their application to reasoning and problem-solving
Experience in Python, Perl, or another scripting language
Experience in a ML or data scientist role with a large technology company
Experience in defining and creating benchmarks for assessing GenAI model performance
Experience working on multi-team, cross-disciplinary projects
Experience applying quantitative analysis to solve business problems and making data-driven business decisions
Experience effectively communicating complex concepts through written and verbal communication

Responsibilities

Own and solve difficult business problems where the solution approach is unclear, delivering high-quality artifacts that directly influence financial decisions for senior leadership
Apply a range of data science methodologies (statistical modeling, machine learning, time series analysis, econometrics) to solve complex forecasting challenges
Design and implement scalable, reliable approaches to extract insights from large, complex datasets across multiple domains
Develop metrics to quantify the benefits of solutions and measure project progress and success
Design and implement Retrieval-Augmented Generation (RAG) systems and LLM-based solutions to enhance financial knowledge retrieval and decision support
Proactively identify and solve challenges related to GenAI solutions including accuracy, latency, and context management
Partner with finance stakeholders, engineers, and other scientists to identify data requirements and deliver solutions that meet customer needs
Write clear, factually correct documents with substantial analytical components; explain technical concepts to non-technical audiences
Provide peer feedback on solutions and results; mentor and teach less experienced data scientists

View full posting on CareerOneStop → ID: 3ec0f3cbe7a2

Machine Learning Engineer, Search & Knowledge Quality

Apple · Seattle, WA

Mid-level Doctorate

2026-05-08

WA 2026-05-08

Requirements

BSc or Masters degree in Machine Learning, Data Science, Computer Science, Information Security, Mathematics, Statistics, or related field.
3+ years of industry related experience, working in collaborate environments
Experience with programming skills in Python,C/C++, GoLand
Experience with ML libraries such as TensorFlow, PyTorch, HuggingFace, AXLearn and Scikit-learn.
Familiarity with integrating ML solutions into production systems and existing workflows at scale; experience with CI/CD workflows and ML pipelines .
Excellent written and verbal communication skills, with the ability to present technical concepts clearly to varied audiences.
Strong problem-solving skills and ability to work independently as well as in a team environment.

Preferred

Ph.D. in a related field.
Experience with state-of-the-art ML methodologies, including LLM fine-tuning, neural network optimization , RL
Strong communication and accountability skills; a hard-working, strong work ethic, and collaboration abilities.
Experimental rigor when training/evaluating LLMs for the purpose of benchmarking LLM optimization algorithms.

Responsibilities

The Search and Knowledge Quality team is redefining how hundreds of millions of users interact with their devices to access information. We are an Applied Machine Learning team pushing the boundaries of artificial intelligence-from query understanding and information retrieval to response ranking and contextual answer generation.
Our team drives innovation by conducting research, building end-to-end solutions, and deploying them at scale to deliver meaningful customer impact across Apple products.
In this role, you will leverage and advance state-of-the-art LLM and ML techniques to better understand user queries and intent, improve document ranking, and generate high-quality answers. You will have end-to-end ownership of features within the Siri Search system, from ideation through production deployment. You will collaborate with industry-leading experts and cross-functional teams across multiple geographies, tackling complex challenges at scale.

View full posting on CareerOneStop → ID: 182f9a6dd20c

Data Scientist

Sedgwick · Boise, ID

Mid-level

2026-05-08

ID 2026-05-08

View full posting on CareerOneStop → ID: e96aaff3185d

Data Scientist

Sedgwick · Cheyenne, WY

Mid-level

2026-05-08

WY 2026-05-08

View full posting on CareerOneStop → ID: 85bbf619229d

Data Scientist

Sedgwick · Las Vegas, NV

Mid-level

2026-05-08

NV 2026-05-08

View full posting on CareerOneStop → ID: 84dfc1748f8e

Data Scientist

Sedgwick · Carson City, NV

Mid-level

2026-05-08

NV 2026-05-08

View full posting on CareerOneStop → ID: dcdd4b2c19f9

Data Scientist

Sedgwick · Bismarck, ND

Mid-level

2026-05-08

ND 2026-05-08

View full posting on CareerOneStop → ID: ece7580bbe03

Data Scientist

Sedgwick · Fargo, ND

Mid-level

2026-05-08

ND 2026-05-08

View full posting on CareerOneStop → ID: 928c77c69133

Data Scientist

Sedgwick · Sioux Falls, SD

Mid-level

2026-05-08

SD 2026-05-08

View full posting on CareerOneStop → ID: d37c8ec6bf4c

Data Scientist

Sedgwick · Rapid City, SD

Mid-level

2026-05-08

SD 2026-05-08

View full posting on CareerOneStop → ID: cc3c3a7d1f74

Data Scientist

Sedgwick · Pierre, SD

Mid-level

2026-05-08

SD 2026-05-08

View full posting on CareerOneStop → ID: cd8d14f91cd7

Data Scientist

Sedgwick · Flagstaff, AZ

Mid-level

2026-05-08

AZ 2026-05-08

View full posting on CareerOneStop → ID: 71f9e0c9c769

Data Scientist

Sedgwick · Phoenix, AZ

Mid-level

2026-05-08

AZ 2026-05-08

View full posting on CareerOneStop → ID: 9bbf3d2aee3b

Data Scientist

Sedgwick · Tucson, AZ

Mid-level

2026-05-08

AZ 2026-05-08

View full posting on CareerOneStop → ID: c71683df86e9

Data Scientist

Sedgwick · Albuquerque, NM

Mid-level

2026-05-08

NM 2026-05-08

View full posting on CareerOneStop → ID: 9c9819a4aa9e

Data Scientist

Sedgwick · Santa Fe, NM

Mid-level

2026-05-08

NM 2026-05-08

View full posting on CareerOneStop → ID: a140b5884af6

Data Scientist

Sedgwick · Lincoln, NE

Mid-level

2026-05-08

NE 2026-05-08

View full posting on CareerOneStop → ID: d0ca31486c33

Data Scientist

Sedgwick · Omaha, NE

Mid-level

2026-05-08

NE 2026-05-08

View full posting on CareerOneStop → ID: db980686deb6

Data Scientist

Sedgwick · Topeka, KS

Mid-level

2026-05-08

KS 2026-05-08

View full posting on CareerOneStop → ID: 2b890c03a28c

Data Scientist

Sedgwick · Wichita, KS

Mid-level

2026-05-08

KS 2026-05-08

View full posting on CareerOneStop → ID: 0d347e4baf28

Data Scientist

Sedgwick · Overland Park, KS

Mid-level

2026-05-08

KS 2026-05-08

View full posting on CareerOneStop → ID: dc358097a569

Data Scientist

Sedgwick · Bartlesville, OK

Mid-level

2026-05-08

OK 2026-05-08

View full posting on CareerOneStop → ID: 814c31a60edb

Data Scientist

Sedgwick · Tulsa, OK

Mid-level

2026-05-08

OK 2026-05-08

View full posting on CareerOneStop → ID: bf4765775900

Data Scientist

Sedgwick · Oklahoma City, OK

Mid-level

2026-05-08

OK 2026-05-08

View full posting on CareerOneStop → ID: dd8da892d9eb

Data Scientist

Sedgwick · Coralville, IA

Mid-level

2026-05-08

IA 2026-05-08

View full posting on CareerOneStop → ID: d3df06fffc70

Data Scientist

Sedgwick · Dubuque, IA

Mid-level

2026-05-08

IA 2026-05-08

View full posting on CareerOneStop → ID: d21fa2bbd1f1

Data Scientist

Sedgwick · Des Moines, IA

Mid-level

2026-05-08

IA 2026-05-08

View full posting on CareerOneStop → ID: 0639927e39de

Data Scientist

Sedgwick · Cedar Rapids, IA

Mid-level

2026-05-08

IA 2026-05-08

View full posting on CareerOneStop → ID: f125515fe03e

Data Scientist

Sedgwick · Saint Louis, MO

Mid-level

2026-05-08

MO 2026-05-08

View full posting on CareerOneStop → ID: 05b12a03fe76

Data Scientist

Sedgwick · Kansas City, MO

Mid-level

2026-05-08

MO 2026-05-08

View full posting on CareerOneStop → ID: acde8c0a6a78

Data Scientist

Sedgwick · Jefferson City, MO

Mid-level

2026-05-08

MO 2026-05-08

View full posting on CareerOneStop → ID: c51041d8ae22

Data Scientist

Sedgwick · Little Rock, AR

Mid-level

2026-05-08

AR 2026-05-08

View full posting on CareerOneStop → ID: 0666aff08b9e

Data Scientist

Sedgwick · Shreveport, LA

Mid-level

2026-05-08

LA 2026-05-08

View full posting on CareerOneStop → ID: 02490aed6860

Data Scientist

Sedgwick · Baton Rouge, LA

Mid-level

2026-05-08

LA 2026-05-08

View full posting on CareerOneStop → ID: 311df3ed69e2

Data Scientist

Sedgwick · New Orleans, LA

Mid-level

2026-05-08

LA 2026-05-08

View full posting on CareerOneStop → ID: 0614391270da

Data Scientist

Sedgwick · Wausau, WI

Mid-level

2026-05-08

WI 2026-05-08

View full posting on CareerOneStop → ID: 1b9e5295d90e

Data Scientist

Sedgwick · Madison, WI

Mid-level

2026-05-08

WI 2026-05-08

View full posting on CareerOneStop → ID: 5ce8fb4671bc

Data Scientist

Sedgwick · Milwaukee, WI

Mid-level

2026-05-08

WI 2026-05-08

View full posting on CareerOneStop → ID: 9019dd4191ac

Data Scientist II (Remote)

Kohl's · Menomonee Falls, WI

Mid-level

2026-05-08

WI 2026-05-08

View full posting on CareerOneStop → ID: 19a4d21c2ec9

Data Scientist

Sedgwick · Jackson, MS

Mid-level

2026-05-08

MS 2026-05-08

View full posting on CareerOneStop → ID: 2d9fae4a0dda

Data Scientist

Sedgwick · Biloxi, MS

Mid-level

2026-05-08

MS 2026-05-08

View full posting on CareerOneStop → ID: 9ecce23896e6

Data Scientist

Sedgwick · Southaven, MS

Mid-level

2026-05-08

MS 2026-05-08

View full posting on CareerOneStop → ID: ebcf3c42d6d5

Data Scientist

Sedgwick · Mobile, AL

Mid-level

2026-05-08

AL 2026-05-08

View full posting on CareerOneStop → ID: 46189fe191cd

Data Scientist

Sedgwick · Montgomery, AL

Mid-level

2026-05-08

AL 2026-05-08

View full posting on CareerOneStop → ID: 890371efd73a

Data Scientist

Sedgwick · Birmingham, AL

Mid-level

2026-05-08

AL 2026-05-08

View full posting on CareerOneStop → ID: fd1b30003c39

Data Scientist

Sedgwick · Knoxville, TN

Mid-level

2026-05-08

TN 2026-05-08

View full posting on CareerOneStop → ID: 41ae017aa06a

Data Scientist

Sedgwick · Memphis, TN

Mid-level

2026-05-08

TN 2026-05-08

View full posting on CareerOneStop → ID: c0c00ec846c7

Data Scientist

Sedgwick · Nashville, TN

Mid-level

2026-05-08

TN 2026-05-08

View full posting on CareerOneStop → ID: f85e6a2b5a73

Data Scientist

Sedgwick · Lexington, KY

Mid-level

2026-05-08

KY 2026-05-08

View full posting on CareerOneStop → ID: f88fbbf3cc19

Data Scientist

Sedgwick · Frankfort, KY

Mid-level

2026-05-08

KY 2026-05-08

View full posting on CareerOneStop → ID: 06d524022996

Data Scientist

Sedgwick · Louisville, KY

Mid-level

2026-05-08

KY 2026-05-08

View full posting on CareerOneStop → ID: 20467bb1c7b1

Data Scientist/Analytics V

Applied Materials · Santa Clara, CA

Mid-level

2026-05-08

WA 2026-05-08

View full posting on CareerOneStop → ID: eae5f7b27a71

Data Scientist

Capgemini · Seattle, WA

Mid-level

2026-05-07

WA 2026-05-07

Requirements

Design, develop, and deploy AI enabled applications aligned to enterprise needs.
Translate business problems into scalable technical solutions.
Build Generative AI solutions using large language models, including RAG and tool enabled workflows.
Apply AI assisted code generation and developer productivity tools for tasks such as code scaffolding, refactoring, documentation, and test generation.
Design and integrate application components using REST APIs, authentication, error handling, and observability best practices.
Deploy and operate AI solutions in production or production adjacent environments, supporting monitoring and reliability.
The base compensation range for this role in the posted location is $70,000- $110,000
Contract Type: Permanent
Seattle, WA, US
Brand: Capgemini
Professional Community: Data & AI

Responsibilities

Capgemini is building a Seattle-based AI Cohort to support strategic enterprise engagements focused on Generative AI, intelligent applications, and advanced analytics. This role combines hands-on AI engineering with a delivery and consulting oriented mindset. You will work closely with business and technical stakeholders to shape, build, and scale AI solutions from early exploration through production delivery. Some engagements may follow a Forward Deployment Engineer (FDE)-style working model, where engineers collaborate closely with client teams during solution design and rollout. However, the role remains broad and well suited for candidates who enjoy combining strong technical problem solving with collaborative, client facing delivery. Many initiatives are centered on enterprise cloud and AI platforms, with a strong preference for Azure based architectures and services, as well as modern developer environments that incorporate AI assisted development and code generation tools.

View full posting on CareerOneStop → ID: c46630f27b7d

Data Scientist, AWS Quick Data

Amazon · Seattle, WA

Mid-level Doctorate

2026-05-07

WA 2026-05-07

Requirements

2+ years of data scientist experience
3+ years of data querying languages (e.g. SQL), scripting languages (e.g. Python) or statistical/mathematical software (e.g. R, SAS, Matlab, etc.) experience
3+ years of machine learning/statistical modeling data analysis tools and techniques, and parameters that affect their performance experience
1+ years of working with or evaluating AI systems experience
1+ years of creating or contributing to mathematical textbooks, research papers, or educational content experience
Master's degree in Science, Technology, Engineering, or Mathematics (STEM), or experience working in Science, Technology, Engineering, or Mathematics (STEM)
Experience applying theoretical models in an applied environment

Preferred

Ph.D. in Science, Technology, Engineering, or Mathematics (STEM)
Knowledge of machine learning concepts and their application to reasoning and problem-solving
Experience in a ML or data scientist role with a large technology company
Experience in defining and creating benchmarks for assessing GenAI model performance
Experience working on multi-team, cross-disciplinary projects
Experience applying quantitative analysis to solve business problems and making data-driven business decisions
Experience effectively communicating complex concepts through written and verbal communication

Responsibilities

In this role, you will leverage data-centric AI principles to assess the impact of data on model performance and the broader machine learning pipeline. You will apply Generative AI techniques to evaluate how well our data represents human language and conduct experiments to measure downstream interactions.
Design and develop comprehensive evaluation and benchmarking datasets for Quick Suite AI-powered features
Leverage LLMs for synthetic data corpora generation; data evaluation and quality assessment using LLM-as-a-judge settings
Create ground truth datasets with high-quality question-answer pairs across diverse domains and use cases
Lead human annotation initiatives and model evaluation audits to ensure data quality and relevance
Develop and refine annotation guidelines and quality frameworks for evaluation tasks
Conduct statistical analysis to measure model performance, identify failure patterns, and guide improvement strategies
Collaborate with ML scientists and engineers to translate evaluation insights into actionable product improvements
Build scalable data pipelines and tools to support continuous evaluation and benchmarking efforts
Contribute to Responsible AI initiatives by developing safety and fairness evaluation datasets

View full posting on CareerOneStop → ID: 451bab6bcd6d

Research Data Scientist, Chrome

Google · Seattle, WA

Mid-level Doctorate

2026-05-07

WA 2026-05-07

Requirements

Master's degree in Statistics, Data Science, Mathematics, Physics, Economics, Operations Research, Engineering, or a related quantitative field.
3 years of work experience using analytics to solve product or business problems, coding (e.g., Python, R, SQL), querying databases or statistical analysis, or a PhD degree.

Preferred

5 years of work experience using analytics to solve product or business problems, coding (e.g., Python, R, SQL), querying databases or statistical analysis, or a PhD degree.

Responsibilities

Chrome's mission is to make the web work better for you. We do this by evolving Chrome, which serves the world and Google as both a product (4 billion plus clients) and a platform (that is: Chromium and related components that advance the open web and open media technologies).
As a platform, Chrome envisions a fast, safe, capable platform and thriving web for generations of users and developers. As a product, Chrome imagines a more helpful, adaptive agent that helps people with their multifaceted needs. Chrome's goal is to redefine browsing by delivering unparalleled safety, speed, efficiency, and ease of use, and integrating with Generative Artificial Intelligence (GenAI) and Google's web products, to understand user needs and provide personalized experiences.
In this role, your work will have tremendous impact throughout Chrome, as you will have an opportunity to work with the many teams that use our systems to gate features and understand users.You will blend research and product expertise to manage issues.
You will leverage a mix of theoretical and practical knowledge in advanced statistical and machine learning (ML) techniques, predictive modeling, human evaluation, experimentation, forecasting, exploratory analysis, and more to drive data-informed innovation, unlock opportunities, and enhance user experiences within Chrome.The US base salary range for this full-time position is $147,000-$211,000 + bonus + equity + benefits. Our salary ranges are determined by role, level, and location. Within the range, individual pay is determined by work location and additional factors, including job-related skills, experience, and relevant education or training. Your recruiter can share more about the specific salary range for your preferred location during the hiring process.
Please note that the compensation details listed in US role postings reflect the base salary only, and do not include bonus, equity, or benefits. Learn more aboutbenefits at Google (https://careers.google.com/benefits/) .
Leverage advanced statistical methods on massive, datasets to extract insights from billions of events and thousands of features across organizational sources.
Analyze intricate product and platform usage patterns, translating data-driven insights into actionable product strategy and engineering decisions.
Collaborate with stakeholders in cross-projects and team settings to identify and clarify business or product questions to answer. Provide feedback to translate and refine business questions into tractable analysis, evaluation metrics, or mathematical models.
Navigate technical or methodological conversations and narrative-telling presentations. Make clear, concise product and engineering recommendations to drive major impact. Use coding and methodology.
Demonstrate an interest and aptitude in data, metrics, analysis, and trends, and applied knowledge of measurement, statistics, and program evaluation.
Information collected and processed as part of your Google Careers profile, and any job applications you choose to submit is subject to Google'sApplicant and Candidate Privacy Policy (./privacy-policy) .

View full posting on CareerOneStop → ID: 45c9a2be5971

Machine Learning Engineer

PLURALSIGHT, LLC · Draper, UT

Mid-level

2026-05-07

UT 2026-05-07

View full posting on CareerOneStop → ID: 5e2e5d6a13bd

GenAI Data Scientist

Deloitte · Gilbert, AZ

Mid-level

2026-05-07

AZ 2026-05-07

View full posting on CareerOneStop → ID: d45daf0357bf

GenAI Data Scientist

Deloitte · Gilbert, AZ

Mid-level

2026-05-07

AZ 2026-05-07

View full posting on CareerOneStop → ID: d717ecce1e17

Data Scientists/BI Developer

Staffingtree, Inc. · Overland Park, KS

Mid-level

2026-05-07

KS 2026-05-07

View full posting on CareerOneStop → ID: 9c95b7a9b22f

DATA SCIENTIST-DIRECT HIRE AUTHORITY

U.S. Air Force - Agency Wide · Oklahoma City, OK

Mid-level

2026-05-07

OK 2026-05-07

View full posting on CareerOneStop → ID: ac7e6bba3451

Machine Learning Scientist

Bayer · Saint Louis, MO

Mid-level

2026-05-07

MO 2026-05-07

View full posting on CareerOneStop → ID: d18d688105cd

data scientist, Data & Analytics (Nashville, TN)

Starbucks · Nashville, TN

Mid-level

2026-05-07

TN 2026-05-07

View full posting on CareerOneStop → ID: d10d1a6b94ad

ASIC Design Engineer II, Annapurna Labs - Cloud-Scale Machine Learning Acceleration

Amazon · Cupertino, CA

Mid-level

2026-05-07

WA 2026-05-07

View full posting on CareerOneStop → ID: 06e11f5ca079

Data Scientist, AWS Quick Data

Amazon · Santa Clara, CA

Mid-level

2026-05-07

WA 2026-05-07

View full posting on CareerOneStop → ID: f8299709a1eb

Machine Learning Engineer, Sign-Up Flow Optimization

Paramount · West Hollywood, CA

Mid-level

2026-05-07

WA 2026-05-07

View full posting on CareerOneStop → ID: 92c4172d6761

Data Science - Forecasting & Lab, SCOT Forecasting & Lab

Amazon · Bellevue, WA

Mid-level Bachelor's

2026-05-06

WA 2026-05-06

Requirements

3+ years of data querying languages (e.g. SQL), scripting languages (e.g. Python) or statistical/mathematical software (e.g. R, SAS, Matlab, etc.) experience
2+ years of data scientist experience
3+ years of machine learning/statistical modeling data analysis tools and techniques, and parameters that affect their performance experience
Bachelor's degree
Experience applying theoretical models in an applied environment

Preferred

Experience in Python, Perl, or another scripting language
Experience in a ML or data scientist role with a large technology company

Responsibilities

Analysis of large amounts of data from different parts of the supply chain and their associated business functions
Improving upon existing machine learning methodologies by developing new data sources, developing and testing model enhancements, running computational experiments, and fine-tuning model parameters for new models
Formalizing assumptions about how models are expected to behave, creating definitions of outliers, developing methods to systematically identify these outliers, and explaining why they are reasonable or identifying fixes for them
Communicating verbally and in writing to business customers with various levels of technical knowledge, educating them about our research, as well as sharing insights and recommendations
Utilizing code (Python, R, Scala, etc.) for analyzing data and building statistical and machine learning models and algorithms
As a Data Scientist in SCOT, you will be tasked to understand and work with cutting edge research to enable the implementation of sophisticated models on big data. As a successful data scientist in the SCOT team, you are an analytical problem solver who enjoys diving into data from various businesses, is excited about investigations and algorithms, can multi-task, and can credibly interface between scientists, engineers and business stakeholders. Your expertise in synthesizing and communicating insights and recommendations to audiences of varying levels of technical sophistication will enable you to answer specific business questions and innovate for the future.

View full posting on CareerOneStop → ID: 7b49a33bff51

Data Scientist

Actalent · Bothell, WA

Mid-level Doctorate

2026-05-06

WA 2026-05-06

Requirements

PMS or equivalent in computational biology, bioinformatics, biostatistics, computer science, genomics or a related field with postdoctoral research experience in Cancer Biology; or MS in cancer biology or related field with established advanced capability and track record in developing and applying computational and bioinformatics methods.
Five years or more of post-PhD academic and/or industry experience working with large, multidimensional, genomics datasets (e.g. NGS, RNA-Seq, transcriptomics, proteomics, flow cytometry, etc.)
Strong foundation in molecular biology and next-generation sequencing technologies (DNA-seq, RNA-seq, targeted panels, WES/WGS)
NGS Data Analysis
Hands-on experience analyzing NGS data end-to-end, including:
o Raw data processing and quality control (FASTQ, BAM/CRAM)
o Alignment, variant calling, and/or expression quantification
o Annotation and interpretation of variants or molecular signatures
Familiarity with common NGS tools and frameworks (e.g., BWA, Bowtie2, GATK, SAMtools, Picard, STAR, Salmon, Kallisto)
Pipeline Development & Automation
Proven experience developing, optimizing, and maintaining reproducible bioinformatics pipelines
Familiarity with workflow management systems (e.g., Nextflow, Snakemake, WDL/Cromwell)
Strong scripting and automation skills in Bash, Python, and R.
Software & Data Engineering
Experience writing code versioned with Git/GitHub
Ability to design modular, scalable, and maintainable analytical workflows
Familiarity with containerization technologies (Docker, Singularity/Apptainer)
Statistical & Computational Skills
Solid understanding of statistics and applied methods relevant to genomics (e.g., differential expression, QC metrics, batch effects)
Experience with data visualization and reporting for scientific and non-scientific audiences
Ability to assess analytical performance, accuracy, and robustness
Computing Environments
Experience working in Linux/Unix environments
Familiarity with high performance computing (HPC) clusters and/or cloud platforms (AWS, GCP, Azure)
Understanding of data storage, data transfer, and compute optimization in large-scale datasets
Experience supporting product development, diagnostics, or translational research in an industry setting
Familiarity with assay validation concepts, analytical performance metrics, and documentation requirements
Exposure to regulated or quality-driven environments (e.g., CLIA, CAP) is a strong plus
Collaboration & Communication
Ability to clearly communicate technical results, assumptions, and limitations to cross functional teams
Experience collaborating with wet lab scientists, software engineers, and program partners
Strong documentation skills for pipelines, analyses, and standard operating procedures

Responsibilities

The Bioinformatics Scientist Contractor will support the Translational Pathology Biomarker Testing Laboratory (TPBTL) within the Translational Medicine department.
The Bioinformatics Scientist applies advanced computational and statistical methods to analyze next generation sequencing (NGS) data to support research, clinical, or translational objectives. This role is responsible for developing, validating, and maintaining scalable, production-ready bioinformatics pipelines
for genomic, transcriptomic, and other high-throughput sequencing applications. Working in a highly collaborative environment, the Bioinformatics Scientist partners closely with wet-lab scientists, pathologists, and bioinformatics team to support data-driven decision-making in both research and CLIA regulated environments.

View full posting on CareerOneStop → ID: 73f2a8b90959

Data Scientist, Advertising, AMPI Measurement

Amazon · Seattle, WA

Mid-level Bachelor's

2026-05-06

WA 2026-05-06

Requirements

3+ years of data querying languages (e.g. SQL), scripting languages (e.g. Python) or statistical/mathematical software (e.g. R, SAS, Matlab, etc.) experience
2+ years of data scientist experience
3+ years of machine learning/statistical modeling data analysis tools and techniques, and parameters that affect their performance experience
Bachelor's degree
Experience applying theoretical models in an applied environment

Preferred

Experience in Python, Perl, or another scripting language
Experience in a ML or data scientist role with a large technology company
Knowledge of relevant statistical measures such as confidence intervals, significance of error measurements, development and evaluation data sets, etc.

Responsibilities

Translate / Interpret:
Partner with cross-functional teams to translate business questions into rigorous causal inference problems
Design observational studies and quasi-experiments to measure marketing effectiveness when traditional A/B tests are infeasible
Work with data engineering to instrument new data pipelines when existing data cannot answer the causal question
Measure / Quantify / Expand:
Own and evolve production attribution models across multiple marketing channels
Build and maintain causal inference pipelines using methods such as Difference-in-Differences, Synthetic Control, Double Machine Learning, and Media Mix Models
Develop scalable PySpark and Python codebases that process large-scale event data
Continuously improve model accuracy through feature engineering, heterogeneity analysis, and sensitivity testing
Explore / Enlighten:
Investigate anomalies in model outputs and deep-dive to identify root causes
Develop automated data quality checks and model diagnostics
Research and prototype next-generation measurement methods
Make Decisions / Recommendations:
Present findings to senior leadership with clear recommendations
Build dashboards and self-service tools that enable stakeholders to explore results independently
Write production-quality Python code for data analysis, model training, and result publishing

View full posting on CareerOneStop → ID: 21012cb296bf

Machine Learning Engineer III

Indeed · Seattle, WA

Mid-level Doctorate

2026-05-06

WA 2026-05-06

Responsibilities

As a Machine Learning Engineer III, you will be a team lead. You will own one of the team's major workstreams, help drive technical direction for the team, and guide other members of the team to achieve product/technical goals. On a daily basis, you will explore data and formulate problem statements, develop and deploy predictive models while monitoring them in production, and guide the team on the same. Additionally, you will partner with cross-functional teams, evangelize your team's work, and stay updated with the latest advancements in the field.
Partner with cross-functional teams to enhance and optimize search algorithms for improved accuracy, relevance, and overall user experience.
Experiment with Proof of Concept Machine Learning model improvements, scale them to production, and run iterative A/B experiments to improve our matching technology while partnering with other teams
Define and clarify project priorities, deliverables, and success criteria in partnership with cross-functional teams.
Act as a bridge between technical and non-technical collaborators, facilitating effective communication and comprehension of project goals and outcomes.
Mentor and grow other software engineers and Machine Learning Engineers across teams
Break down larger Machine Learning initiatives into pieces that deliver incremental business value and guide the team through implementing them
Represent Indeed at major Machine Learning conferences, such as Neural Information Processing Systems (NeurIPS), the International Conference on Machine Learning (ICML), and the International Conference on Learning Representations (ICLR).
*Skills/Competencies
Requires a Bachelor's degree in Computer Science, Mathematics, or Statistics, and a minimum of 8 years of related experience; or a Master's degree with a minimum of 6 years of experience; or a PhD with 3 years experience
Prior success in deploying impactful Machine Learning solutions to large-scale production systems, while partnering across teams
Solid knowledge of data structures and algorithms
Sense of ownership and accountability as a key contributor in the technical and product domains
Knowledge and practical experience working on Deep Learning Libraries (like Torch, Tensorflow, etc.)
Excellent written and verbal communication in English, effective with technical and business audiences

View full posting on CareerOneStop → ID: f2ee8858280e

Machine Learning Engineer III

Indeed · Portland, OR

Mid-level Doctorate

2026-05-06

WA 2026-05-06

Responsibilities

As a Machine Learning Engineer III, you will be a team lead. You will own one of the team's major workstreams, help drive technical direction for the team, and guide other members of the team to achieve product/technical goals. On a daily basis, you will explore data and formulate problem statements, develop and deploy predictive models while monitoring them in production, and guide the team on the same. Additionally, you will partner with cross-functional teams, evangelize your team's work, and stay updated with the latest advancements in the field.
Partner with cross-functional teams to enhance and optimize search algorithms for improved accuracy, relevance, and overall user experience.
Experiment with Proof of Concept Machine Learning model improvements, scale them to production, and run iterative A/B experiments to improve our matching technology while partnering with other teams
Define and clarify project priorities, deliverables, and success criteria in partnership with cross-functional teams.
Act as a bridge between technical and non-technical collaborators, facilitating effective communication and comprehension of project goals and outcomes.
Mentor and grow other software engineers and Machine Learning Engineers across teams
Break down larger Machine Learning initiatives into pieces that deliver incremental business value and guide the team through implementing them
Represent Indeed at major Machine Learning conferences, such as Neural Information Processing Systems (NeurIPS), the International Conference on Machine Learning (ICML), and the International Conference on Learning Representations (ICLR).
*Skills/Competencies
Requires a Bachelor's degree in Computer Science, Mathematics, or Statistics, and a minimum of 8 years of related experience; or a Master's degree with a minimum of 6 years of experience; or a PhD with 3 years experience
Prior success in deploying impactful Machine Learning solutions to large-scale production systems, while partnering across teams
Solid knowledge of data structures and algorithms
Sense of ownership and accountability as a key contributor in the technical and product domains
Knowledge and practical experience working on Deep Learning Libraries (like Torch, Tensorflow, etc.)
Excellent written and verbal communication in English, effective with technical and business audiences

View full posting on CareerOneStop → ID: ea05576560d7

Machine Learning Engineer III

Indeed · Boise, ID

Mid-level

2026-05-06

ID 2026-05-06

View full posting on CareerOneStop → ID: bd4947141ef6

Machine Learning Engineer III

Indeed · Helena, MT

Mid-level

2026-05-06

MT 2026-05-06

View full posting on CareerOneStop → ID: c29d6adb7163

Machine Learning Engineer III

Indeed · Cheyenne, WY

Mid-level

2026-05-06

WY 2026-05-06

View full posting on CareerOneStop → ID: ebc6abb397fe

Machine Learning Engineer

Extra Space Storage · Salt Lake City, UT

Mid-level

2026-05-06

UT 2026-05-06

View full posting on CareerOneStop → ID: b98af4744e49

Machine Learning Engineer III

Indeed · Salt Lake City, UT

Mid-level

2026-05-06

UT 2026-05-06

View full posting on CareerOneStop → ID: 61931e350b34

Machine Learning Engineer III

Indeed · Las Vegas, NV

Mid-level

2026-05-06

NV 2026-05-06

View full posting on CareerOneStop → ID: 576d7e4724de

Machine Learning Engineer III

Indeed · Bismarck, ND

Mid-level

2026-05-06

ND 2026-05-06

View full posting on CareerOneStop → ID: ef56e765a344

Machine Learning Engineer III

Indeed · Sioux Falls, SD

Mid-level

2026-05-06

SD 2026-05-06

View full posting on CareerOneStop → ID: 2f33dad3e694

Machine Learning Engineer III

Indeed · Scottsdale, AZ

Mid-level

2026-05-06

AZ 2026-05-06

View full posting on CareerOneStop → ID: c4fa7b874ce5

Machine Learning Engineer III

Indeed · Albuquerque, NM

Mid-level

2026-05-06

NM 2026-05-06

View full posting on CareerOneStop → ID: ffa8f27b04fe

AI/ML Engineer

Lockheed Martin · Littleton, CO

Mid-level

2026-05-06

CO 2026-05-06

View full posting on CareerOneStop → ID: 3b0bdb83ae36

Machine Learning Engineer III

Indeed · Denver, CO

Mid-level

2026-05-06

CO 2026-05-06

View full posting on CareerOneStop → ID: 5cad1787a878

Machine Learning Engineer III

Indeed · Omaha, NE

Mid-level

2026-05-06

NE 2026-05-06

View full posting on CareerOneStop → ID: 1c51f6285cac

Machine Learning Engineer III

Indeed · Kansas City, KS

Mid-level

2026-05-06

KS 2026-05-06

View full posting on CareerOneStop → ID: 540a16731d89

Machine Learning Engineer III

Indeed · Oklahoma City, OK

Mid-level

2026-05-06

OK 2026-05-06

View full posting on CareerOneStop → ID: d163c9bfab6b

Machine Learning Engineer III

Indeed · Saint Paul, MN

Mid-level

2026-05-06

MN 2026-05-06

View full posting on CareerOneStop → ID: 9f6f871c89d2

Machine Learning Engineer III

Indeed · Des Moines, IA

Mid-level

2026-05-06

IA 2026-05-06

View full posting on CareerOneStop → ID: a60ba4f0761a

Machine Learning Engineer III

Indeed · Saint Louis, MO

Mid-level

2026-05-06

MO 2026-05-06

View full posting on CareerOneStop → ID: d2a3d7adc13b

Machine Learning Engineer III

Indeed · Little Rock, AR

Mid-level

2026-05-06

AR 2026-05-06

View full posting on CareerOneStop → ID: 88557049ff17

Machine Learning Engineer III

Indeed · Baton Rouge, LA

Mid-level

2026-05-06

LA 2026-05-06

View full posting on CareerOneStop → ID: 223fad402a3b

Machine Learning Engineer III

Indeed · Milwaukee, WI

Mid-level

2026-05-06

WI 2026-05-06

View full posting on CareerOneStop → ID: ba9343f8c33f

Machine Learning Engineer III

Indeed · Chicago, IL

Mid-level

2026-05-06

IL 2026-05-06

View full posting on CareerOneStop → ID: 24463c171f65

Supply Chain Data Scientist - RadioPharma US & Canada

GE HealthCare · Chicago, IL

Mid-level

2026-05-06

IL 2026-05-06

View full posting on CareerOneStop → ID: de263d79ed4e

Machine Learning Engineer III

Indeed · Jackson, MS

Mid-level

2026-05-06

MS 2026-05-06

View full posting on CareerOneStop → ID: b4389d6bb9c0

Machine Learning Engineer III

Indeed · Huntsville, AL

Mid-level

2026-05-06

AL 2026-05-06

View full posting on CareerOneStop → ID: a6c4b804e707

Machine Learning Engineer III

Indeed · Nashville, TN

Mid-level

2026-05-06

TN 2026-05-06

View full posting on CareerOneStop → ID: d8282d429ccb

Machine Learning Engineer III

Indeed · Louisville, KY

Mid-level

2026-05-06

KY 2026-05-06

View full posting on CareerOneStop → ID: f27168bd2b96

Data Scientist II

Applied Materials · Santa Clara, CA

Mid-level

2026-05-06

WA 2026-05-06

View full posting on CareerOneStop → ID: fec16eb0a8bc

Data Science Consultant

Deloitte · Seattle, WA

Mid-level Master's

2026-05-05

WA 2026-05-05

Requirements

A Bachelor's in a quantitative field (engineering, mathematics, physics, machine learning, statistics or computer science) are the ideal candidates.
At least 2+ years of industry experience outside of academia
Ability to travel 30%, on average, based on the work you do and the client and industries/sectors you serve
Must be legally authorized to work in the United States without the need for employer sponsorship now or at any time in the future

Preferred

A Master's in a quantitative field (engineering, mathematics, physics, machine learning, statistics or computer science) are the ideal candidates.
Good problem decomposition skills and autonomy when faced with solving data problems
Experience manipulating large marketing data sets and performing ETL
Excellent hands-on knowledge of modeling approaches such as Boosted Trees, Logistic regression, Classification Techniques, Unsupervised models, LLM, and experimental design
Experience with large data sets generated in the Ad Tech or Marketing technology spaces
Excellent verbal and written communication skills are required. Candidates must be proficient in conveying complex data insights in an accessible manner to a non-technical audience, including those outside the data science department. This entails adeptness in tailoring messages effectively and choosing appropriate visual aids to facilitate understanding.
Proficiency in high level scripting language, such as Python or R
Understanding of the strategic application of data science methodologies in driving valuable business outcomes for large enterprises
If you have code in the open domain (for example GitHub) or have written about AI/DS please share this with us
Experience with Deep Learning architectures and/or Reinforcement Learning
The wage range for this role takes into account the wide range of factors that are considered in making compensation decisions including but not limited to skill sets; experience and training; licensure and certifications; and other business and organizational needs. The disclosed range estimate has not been adjusted for the applicable geographic differential associated with the location at which the position may be filled. At Deloitte, it is not typical for an individual to be hired at or near the top of the range for their role and compensation decisions are dependent on the facts and circumstances of each case. A reasonable estimate of the current range is $93,000 to $171,300.
You may also be eligible to participate in a discretionary annual incentive program, subject to the rules governing the program, whereby an award, if any, depends on various factors, including, without limitation, individual and organizational performance.

View full posting on CareerOneStop → ID: 8fa5ec90c051

Data Science Consultant

Deloitte · Tempe, AZ

Mid-level

2026-05-05

AZ 2026-05-05

View full posting on CareerOneStop → ID: 15820b0f2b56

Data Science Consultant

Deloitte · Denver, CO

Mid-level

2026-05-05

CO 2026-05-05

View full posting on CareerOneStop → ID: b65fafc760ba

Data Science Consultant

Deloitte · Minneapolis, MN

Mid-level

2026-05-05

MN 2026-05-05

View full posting on CareerOneStop → ID: 9c9720dd7e49

Data Science Consultant

Deloitte · Kansas City, MO

Mid-level

2026-05-05

MO 2026-05-05

View full posting on CareerOneStop → ID: d005f8449789

Data Science Consultant

Deloitte · Saint Louis, MO

Mid-level

2026-05-05

MO 2026-05-05

View full posting on CareerOneStop → ID: 7b95faf52216

Machine Learning Engineers II

Centene Corporation · Clayton, MO

Mid-level

2026-05-05

MO 2026-05-05

View full posting on CareerOneStop → ID: 84d0e0170f82

Data Science Consultant

Deloitte · Chicago, IL

Mid-level

2026-05-05

IL 2026-05-05

View full posting on CareerOneStop → ID: 4eb8fc73d873

Data Science Consultant

Deloitte · Nashville, TN

Mid-level

2026-05-05

TN 2026-05-05

View full posting on CareerOneStop → ID: fa63468ded0d

Data Scientist II, SCOT OSS - Sourcing Execution & Performance

Amazon · Bellevue, WA

Mid-level Master's

2026-05-02

WA 2026-05-02

Requirements

2+ years of data scientist or similar role involving data extraction, analysis, statistical modeling and communication experience
2+ years of data querying languages (e.g. SQL, Hadoop/Hive) experience
3+ years of machine learning/statistical modeling data analysis tools and techniques, and parameters that affect their performance experience
Master's degree in a quantitative field, or Bachelor's degree and 5+ years of a quantitative field such as statistics, mathematics, data science, business analytics, economics, finance, engineering, or computer science experience
Experience applying theoretical models in an applied environment

Preferred

Experience in Python, Perl, or another scripting language
Experience in a ML or data scientist role with a large technology company

Responsibilities

Collaborate with product managers, science, and engineering teams to design and implement model solutions for Sourcing Execution & Performance systems
Use large datasets or experiments to make causal inferences or predictions
Work with engineers to automate science analysis processes and build scalable measurement solutions
Interpret data, write reports, and make actionable recommendations
Drive technical standards and best practices for the team's Science solutions
Mentor and provide technical guidance to other team members on complex projects
Amazon offers a full range of benefits that support you and eligible family members, including domestic partners and their children. Benefits can vary by location, the number of regularly scheduled hours you work, length of employment, and job status such as seasonal or temporary employment.
The benefits that generally apply to regular, full-time employees include:
Medical, Dental, and Vision Coverage
Maternity and Parental Leave Options
Paid Time Off (PTO)
If you are not sure that every qualification on the list above describes you exactly, we'd still love to hear from you!
At Amazon, we value people with unique backgrounds, experiences, and skillsets. If you're passionate about this role and want to make an impact on a global scale, please apply!

View full posting on CareerOneStop → ID: 7eca1a38e8a5

Data Scientist, SCOT Forecasting and Labs - CIV Team

Amazon · Bellevue, WA

Mid-level Bachelor's

2026-05-02

WA 2026-05-02

Requirements

3+ years of data querying languages (e.g. SQL), scripting languages (e.g. Python) or statistical/mathematical software (e.g. R, SAS, Matlab, etc.) experience
3+ years of data scientist experience
3+ years of machine learning/statistical modeling data analysis tools and techniques, and parameters that affect their performance experience
Bachelor's degree
Experience applying theoretical models in an applied environment

Preferred

Experience in Python, Perl, or another scripting language
Experience in a ML or data scientist role with a large technology company

View full posting on CareerOneStop → ID: fec7b9a678c8

Data Scientist III - AMZ9971313

IMDB.COM, INC. · Seattle, WA

Mid-level Master's

2026-05-02

WA 2026-05-02

[MULTIPLE POSITIONS AVAILABLE]{.underline} [Employer]{.underline}: IMDB.COM, INC. [Offered Position]{.underline}: Data Scientist III [Job Location]{.underline}: Seattle, Washington [Job Number]{.underline}: AMZ9971313 [

View full posting on CareerOneStop → ID: 41a7dcc4c83f

Machine Learning Engineer, Firefly Services

Adobe Inc. · Seattle, WA

Mid-level Doctorate

2026-05-02

WA 2026-05-02

Requirements

MS or PhD in Computer Science, Machine Learning, or a related field-or equivalent industry experience.
1-3+ years of experience in machine learning, including production-scale deployments.
1-3+ years of experience leading large-scale, GPU-intensive GenAI systems (training, inference, and optimization).
Experience with GenAI frameworks and tools such asPyTorch, CUDA, Triton, TensorRT,Nvidia Dynamo, and Python.
Good understanding of generative model architectures, includingdiffusion models, transformers, and GANs.
Good communication and leadership skills, with a track record of driving alignment in matrixed organizations.

Preferred

Experience withmodel serving, inference, orchestration, and GPU resource managementin large-scale environments.
Hands-on expertise inKubernetes, distributed systems, and MLOps platforms.

Responsibilities

Adobe Firefly'sGenerative AI Servicesteam is seekingSeniorMachine Learning Engineersfor our GenAI Services area. In this high-impact role, you will work with a team of talented engineers in building scalable, high-performance generative AI systems-powering features across Adobe products like Firefly, Photoshop, Illustrator, Express, Stock, and Premiere.You will design and develop efficient inference pipelines, optimize models for latency and through at inference, and build APIs and ecosystems that integrate both Adobe's first-party and third-party generative models into Adobe suite of products that serve individual and enterprise customers. You will tackle Adobe's most complex engineering challenges at the forefront of the the industry, set technical direction, and mentor other ML engineers.Job Responsibilities
Design and evelopmentof core GenAI services and APIs that integrate a wide range of generative models into Adobe's flagship products.
Design and buildML workflows for enterprise-scale model customization, serving, and ecosystem integration.
Collaboratewith Adobe Research and other model developer teams with a focus on model inference strategies and productization of those model
Build and optimizeGPU-accelerated pipelines for both (customized) model training and inference-prioritizing performance, scalability, and reliability.
Foster a culture of innovation, technical excellence, and continuous improvement across the organization.

View full posting on CareerOneStop → ID: 0948b122b9a9

Data Scientist

Vail Resorts · Broomfield, CO

Mid-level

2026-05-02

CO 2026-05-02

View full posting on CareerOneStop → ID: bb2dbcd00f34

Data Scientist, SPX AI Lab, SPX Science

Amazon · Seattle, WA

Mid-level Master's

2026-05-01

WA 2026-05-01

Requirements

2+ years of data scientist experience
3+ years of data querying languages (e.g. SQL), scripting languages (e.g. Python) or statistical/mathematical software (e.g. R, SAS, Matlab, etc.) experience
3+ years of machine learning/statistical modeling data analysis tools and techniques, and parameters that affect their performance experience
1+ years of working with or evaluating AI systems experience
Master's degree in Science, Technology, Engineering, or Mathematics (STEM), or experience working in Science, Technology, Engineering, or Mathematics (STEM)

Preferred

Knowledge of machine learning concepts and their application to reasoning and problem-solving
Experience in a ML or data scientist role with a large technology company
Experience in defining and creating benchmarks for assessing GenAI model performance
Experience working on multi-team, cross-disciplinary projects
Experience applying quantitative analysis to solve business problems and making data-driven business decisions
Experience effectively communicating complex concepts through written and verbal communication

Responsibilities

Own the product vision, strategy, and roadmap for a key Seller Assistant capability area.
Define and ship agentic experiences - reasoning, planning, memory, context engineering - that solve hard seller problems at scale.
Partner with scientists and engineers to translate frontier AI research into production-grade features sellers trust and depend on.
Design rigorous evaluation frameworks - automated and human-in-the-loop - to measure agent quality, accuracy, and business impact.
Deep-dive into seller data, identify unmet needs, and write compelling PRFAQs that set the direction for your team.
Drive cross-functional alignment across science, engineering, UX, and business teams to deliver with speed and quality.

View full posting on CareerOneStop → ID: afc613081312

Machine Learning Engineer (multiple openings)

ADOBE SYSTEMS INC · Seattle, WA

Mid-level Master's

2026-05-01

WA 2026-05-01

Use machine language and statistical modeling to evaluate and develop algorithms to improve Adobe products and systems. Duties include: design, develop, and deploy large-scale machine learning systems; architect and develop end-to-end machine learning systems using innovative architectures; develop

View full posting on CareerOneStop → ID: 8335434df4e6

AI and ML Engineer

BOOZ, ALLEN & HAMILTON, INC. · Offutt A F B, NE

Mid-level

2026-05-01

NE 2026-05-01

View full posting on CareerOneStop → ID: 0d89150ecd84

Clinical Data Scientist, Human Capital

Community Health Systems · Franklin, TN

Mid-level

2026-05-01

TN 2026-05-01

View full posting on CareerOneStop → ID: a5fa0a719e55

Data Scientist Level lll

Mb Solutions, Inc. · Indian Springs, NV

Mid-level

2026-04-30

NV 2026-04-30

View full posting on CareerOneStop → ID: 17cba48ff872

Clinical Data Scientist, Patient Experience

Community Health Systems · Franklin, TN

Mid-level

2026-04-30

TN 2026-04-30

View full posting on CareerOneStop → ID: 6515c9b026bc

Machine Learning Engineer, Video Search Team

Apple · Seattle, WA

Mid-level Master's

2026-04-29

WA 2026-04-29

Requirements

4+ years of industry or practical experience in machine learning, NLP, IR, or more recently Large Language Model ( LLMs).
Strong programming skills in Python, Java and Go for building scalable ML systems.
Hands-on expertise in ML libraries such as PyTorch, JAX, TensorFlow for model training and deployment.
Ability to translate product goals into technical solutions, improving user experience.
Strong communication, collaboration, and analytical problem-solving skills.
In-depth knowledge of search and information retrieval fundamentals, including indexing and ranking. Experience with retrieval and ranking algorithms and building big data pipelines using Hadoop, Java, Scala, Spark and more.
Industrial experience in search, classification, recommendation systems, or related fields.
Familiarity with A/B testing and data-driven product development.
Passionate about creating products loved by customers at Apple.
Master's degree or higher (or equivalent practical experience) in Computer Science, Machine Learning, Natural Language Processing, Artificial Intelligence, or a related field.

Preferred

Experience with search or recommendation systems, and semantic retrieval or vector databases.
Expertise in transformer architectures, embeddings, and retrieval or ranking models.
Experience in applying or fine-tuning LLMs for understanding and generation tasks. Familiarity with prompt design, context management, RAG and Agentic architectures and solutions.
Exposure to evaluation and safety frameworks for LLM-based systems.
Knowledge of reinforcement learning and other modern post training practices for LLMs.
Passion for developing intelligent, human-centered experiences to enhance content discovery.

Responsibilities

The Apple Services Engineering AI/ML organization is hiring a Machine Learning Engineer to join the Video Search team.
Our team builds the core intelligence that powers search discovery experiences in the Apple TV App, Siri, and Spotlight cross platforms, helping users effortlessly find and enjoy the content they love. We are a collaborative, high-impact team that values innovation, craftsmanship, and end-to-end ownership from idea to launch. Our systems combine large-scale data, modern retrieval and ranking models, and a deep commitment to user privacy.
Join us, you'll develop scalable systems and machine learning models that drive search relevance, personalization, and understanding of content at scale. Working closely with cross-functional partners in product and design, you'll translate cutting-edge research in advanced machine learning and generative AI into secure and delightful production features used by millions every day.
As a Machine Learning Engineer on the Video Search team, within the Apple Services Engineering AI/ML organization, you will design and deploy large-scale ML systems that power search and discovery across Apple platforms.
You'll apply machine learning, natural language understanding, and generative AI to model user intent and deliver relevant, personalized results. Your work will involve building and optimizing cutting edge data processing, ML models, retrieval pipelines, and ranking systems that operate at global scale and under strict privacy standards.
This is a hands-on role where you will collaborate closely with cross-functional teams to bring advanced ML technologies into production-shaping how users discovery content they love in Apple TV app, cross Apple TV partners on Apple Platforms, also through Siri and Spotlight.

View full posting on CareerOneStop → ID: 455b17ba2d5c

Marketing Data Scientist 4

Bucher & Christian Consulting, Inc. dba BCforward (BCF) · Redmond, WA

Mid-level

2026-04-29

WA 2026-04-29

Requirements

1.Marketing analytics
Databricks is strongly preferred for candidates to have but not required

Responsibilities

We are seeking a Marketing Data Scientist to join our dynamic team. The ideal candidate will have strong experience in marketing analytics, attribution modeling, experimentation, and stakeholder engagement, and a proven ability to translate complex results into clear, actionable recommendations that drive budget decisions and marketing effectiveness.
Measure drivers of player acquisition, reactivation, and long-term value across marketing channels.
Own campaign post-mortems, attribution modeling, and funnel analysis to connect spend and impressions to engagement and monetization outcomes.
Partner with Growth Marketing and Finance to inform budget allocation and build scalable measurement frameworks.
Engage stakeholders through presentations, training, and insight-driven discussions to influence decisions.
Determine data requirements and implement best practices for data manipulation, storage, and analysis strategies.
Design, implement, automate, and maintain large-scale enterprise ETL processes supporting marketing analytics.
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View full posting on CareerOneStop → ID: ccd57eb9e398

Monetization Data Scientist 4

Bucher & Christian Consulting, Inc. dba BCforward (BCF) · Redmond, WA

Mid-level

2026-04-29

WA 2026-04-29

Requirements

Python/Databricks (4+ years)
presentation and communication (5+ years)
attribution and causal inference (4+ years)

Responsibilities

We are seeking a Data Scientist to join our dynamic team supporting a gaming monetization portfolio. The ideal candidate will have strong experience in advanced analytics, experimentation, and predictive modeling in Python and SQL on Databricks and a proven ability to optimize subscription and digital content revenue while protecting player experience.
Apply analytics and experimentation to optimize monetization across subscriptions, marketplace content sales, and creator-driven offerings.
Build LTV and churn propensity models and analyze cross-product spend behavior to inform pricing and packaging.
Design, execute, and interpret A/B tests on pricing, promotions, and UX changes; deliver clear readouts and recommendations.
Partner with Product, Finance, and Marketing to translate business questions into data solutions and influence roadmap decisions.
Design, implement, automate, and maintain scalable ETL pipelines and data models for experimentation and reporting.
Develop logical and physical data definitions and collaborate on database optimization and governance.
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View full posting on CareerOneStop → ID: 4d30096e1673

Data Scientist

Booz Allen Hamilton · Aurora, CO

Mid-level

2026-04-29

CO 2026-04-29

View full posting on CareerOneStop → ID: 10b88733d9f2

Data Scientist

Vizient, Inc. · Centennial, CO

Mid-level

2026-04-29

CO 2026-04-29

View full posting on CareerOneStop → ID: 2fd250b23915

Machine Learning Scientist - Personalization Science, Apple Media Products

Apple · Seattle, WA

Mid-level Doctorate

2026-04-28

WA 2026-04-28

Requirements

6+ years of relevant work experience.
Deep knowledge of machine learning powered personalization algorithms, design patterns and tools. In particular, this includes deep learning, reinforcement learning and unsupervised learning methods.
Knowledge of generative artificial intelligence applied to recommendation systems.
Practical real-world experience with building scalable recommendation systems.
Proven grasp of the open-source Python ML/AI tech stack, including Tensorflow, pytorch, scikit-learn, numpy-scipy-pandas.
Technical competence in production-quality software development.
Familiarity with big data technologies.
Strong written & oral communication skills.
Master's in a quantitative field, including Computer Science, Maths, Statistics, Physics, etc.

Preferred

PhD in a quantitative field, including Computer Science, Maths, Statistics, Physics, etc.

Responsibilities

Wonder how Apple's Media Products show relevant search results and recommendations across Apple's media offerings - including App Store, Apple TV, Apple Music, Apple Podcasts, and Apple Books? Come join us! Research, design and develop machine learning models that personalize the App Store for billions of users worldwide! Propose, prototype and evaluate algorithm improvements. Build large-scale personalized recommender systems for Apple Music, Apps & Games Recommendations, Video, Podcast and Books Recommendations. See your work touch the lives of billions of Apple users worldwide.
The Apple Services Engineering team is one of the most exciting examples of Apple's long-held passion for combining art and technology. We are the people who power the App Store, Apple TV, Apple Music, Apple Podcasts, and Apple Books. And we do it on a massive scale, meeting Apple's high expectations with high performance, to deliver a huge variety of entertainment in over 35 languages to more than 150 countries. Our scientists and engineers build secure, end-to-end solutions powered by machine learning. Thanks to Apple's unique integration of hardware, software, and services, designers, scientists and engineers here partner to get behind a single unified vision. That vision always includes a deep commitment to strengthening Apple's privacy policy, one of Apple's core values. Although services are a bigger part of Apple's business than ever before, these teams remain small, flexible, and multi-functional, offering greater exposure to the array of opportunities here.
We are looking for a world-class researcher to help us solve challenging problems in personalization science using the latest advances in machine learning. With your expertise, we want to develop novel solutions to power personalized experiences across the App Store that enrich the lives of our customers. You will have the incredible opportunity to see your solutions deployed at Apple's truly incredible global scale.

View full posting on CareerOneStop → ID: 9dc66a3f353b

Machine Learning Tools Engineer, SIML

Apple · Seattle, WA

Mid-level Bachelor's

2026-04-28

WA 2026-04-28

Requirements

Bachelor's degree in Computer Science, Engineering, or a related technical field; or equivalent practical experience.
3+ years of experience in software development with strong Python proficiency.
Familiarity with machine learning fundamentals and frameworks (e.g., PyTorch, TensorFlow, JAX).
Experience with Linux systems, containers (Docker), and version control (Git).
Strong debugging, analytical, and problem-solving skills.
Comfortable operating at the intersection of research and product, coordinating across teams with competing timelines and technical constraints.

Preferred

Prior experience in an ML platform, infrastructure, or productivity tools team.
Experience building internal SDKs, CLIs, or automation frameworks for ML or data workflows.
Exposure to distributed training, experiment tracking, or model serving infrastructure.
Experience supporting large internal or external developer communities.

Responsibilities

Are you passionate about Generative AI? Are you interested in working on groundbreaking generative modeling technologies to enrich billions of people? We are the Intelligence System Experience (ISE) team within Apple's software organization. The team operates at the intersection of multimodal machine learning and system experiences. Our multidisciplinary ML teams focus on a broad spectrum of areas, including Visual Generative Foundation Models, Multimodal Understanding, Visual Understanding of People, Text, Handwriting, and Scenes, Personalization, Knowledge Extraction, Conversation Analysis, Behavioral Modeling for Proactive Suggestions, and Privacy-Preserving Learning. These innovations form the foundation of the seamless, intelligent experiences our users enjoy every day.
We are looking for a Machine Learning Tools Engineer to help build and evolve the infrastructure, tools, and libraries that power model development and deployment across our organization. The ideal candidate combines strong software engineering fundamentals with ML domain understanding and a deep passion for improving developer experience. You'll partner closely with researchers, ML engineers, and infra teams to design tools that make training, experimentation, evaluation and inference seamless and efficient. This role is hands-on, user-focused, and requires a balance of building scalable systems and operationally supporting a large and growing user base.
As a Machine Learning Tools Engineer, you will:
Design, develop, and maintain core ML infrastructure components (training pipelines, experiment tracking, deployment tooling, and monitoring systems).
Collaborate with ML practitioners to identify pain points and translate them into productized solutions that enhance productivity and reliability.
Build and maintain Python-based SDKs, CLIs, and APIs that simplify how ML engineers interact with compute, data, and models.
Ensure tools are robust, performant, and user-friendly, with strong observability and documentation.
Partner with infrastructure, MLOps, and platform teams to ensure end-to-end system integration and smooth scaling.
This is a highly collaborative role that requires curiosity, empathy for users, and a drive to make ML development frictionless.

View full posting on CareerOneStop → ID: 226b9e03ca70

Data Scientist II - AI Assurance Researcher

Pacific Northwest National Laboratory · Seattle, WA

Mid-level Doctorate

2026-04-25

WA 2026-04-25

Requirements

BS/BA and 2 years of relevant experience -OR-
U.S. Citizenship
Background Investigation: Applicants selected will be subject to a Federal background investigation and must meet eligibility requirements for access to classified matter in accordance with 10 CFR 710, Appendix B.
As a national laboratory, PNNL is responsible for adhering to the Homeland Security Presidential Directive 12 (HSPD-12) and Department of Energy (DOE) Order 473.1A, which require new employees to obtain and maintain a HSPD-12 Personal Identify Verification (PIV) Credential. To obtain this credential, new employees must successfully complete the applicable tier of federal background investigation post hire and receive a favorable federal adjudication. The tier of federal background investigation will be determined by job duties and national security or public trust responsibilities associated with the job. All tiers of investigation include a declaration of illegal drug activities, including use, supply, possession, or manufacture within the last 1 to 7 years (depending on the applicable tier of investigation). Illegal drug activities include marijuana and cannabis derivatives, which are still considered illegal under federal law, regardless of state laws.
For foreign national candidates:
If you have not resided in the U.S. for three consecutive years, you are not eligible for the PIV credential and instead will need to obtain a favorable Local Site Specific Only (LSSO) Federal risk determination to maintain employment. Once you meet the three-year residency requirement thereafter, you will be required to obtain a PIV credential to maintain employment. The tier of federal background investigation required to obtain the PIV credential will be determined by job duties at the time you become eligible for the PIV credential.
Please be aware that the Department of Energy (DOE) prohibits DOE employees and contractors from having any affiliation with the foreign government of a country DOE has identified as a "country of risk" without explicit approval by DOE and Battelle. If you are offered a position at PNNL and currently have any affiliation with the government of one of these countries, you will be required to disclose this information and recuse yourself of that affiliation or receive approval from DOE and Battelle prior to your first day of employment.
*Rockstar Rewards

Preferred

Degree in computer science, engineering, mathematics, or a related field.
Familiarity with the current ML research landscape, particularly in explainable AI, adversarial machine learning, AI safety, and the science of deep learning.
Hands-on experience analyzing the internal structures of deep learning models, particularly large language models and large vision models.
Proficiency in PyTorch and associated deep learning libraries.
Experience designing and executing experiments on HPC systems.
Experience in translating research prototypes into deployable tools and capabilities.
Demonstrated strong communication and collaboration skills, with the ability to work effectively in a multi-disciplinary team environment.

Responsibilities

PNNL is seeking a Data Scientist II - AI Assurance Researcher who has experience in understanding, exploring, and manipulating the internal mechanics and behaviors of AI models and can provide valuable insights into the decision boundaries and mathematical fingerprints of data properties. The selected candidate should have extensive experience training models, accessing and working with data embeddings, the ability to derive theoretical queries from empirical results, and demonstrate the capacity to translate research papers and findings into mission relevant insights and tools.
Designs and executes rigorous ML experiments following community best practices, including large-scale training and evaluation on HPC infrastructure.
Evaluates AI systems across multiple dimensions, including standard performance metrics, generalization, robustness, and out-of-distribution behavior.
Analyzes the internal structures and representations of deep learning models, with emphasis on large language models and large vision models.
Assesses empirical results to identify trends, inform research direction, and recommend next steps.
Writes high-quality, well-documented research code that supports reproducibility and collaboration.
Contributes to publications and technical reports that communicate findings to both internal and external audiences.
Collaborates with senior researchers, engineers, and cross-functional teams to integrate research into broader systems and workflows.
Conducts work in secure environments with adherence to operational security requirements.
*This position is based in either Richland, WA or Seattle, WA and requires an onsite presence.

View full posting on CareerOneStop → ID: 8fb806ff29bc

Data Scientist, Labs, SCOT Forecasting and Labs

Amazon · Bellevue, WA

Mid-level Doctorate

2026-04-25

WA 2026-04-25

Requirements

3+ years of machine learning, statistical modeling, data mining, and analytics techniques experience
3+ years of data querying languages (e.g. SQL), scripting languages (e.g. Python) or statistical/mathematical software (e.g. R, SAS, Matlab, etc.) experience
3+ years of data scientist experience
Bachelor's degree

Preferred

Master's degree, or PhD
Natural curiosity and desire to learn

Responsibilities

Partner with customer teams to design rigorous large-scale experiments (such as randomized controlled trials and quasi-experiments) to evaluate policy updates and model improvements across millions of products, hundreds of fulfillment nodes, and diverse business contexts
Lead the end-to-end experimentation lifecycle, from hypothesis formulation through analysis and stakeholder alignment, to inform production rollout decisions
Advance causal inference methodology for supply chain settings, including treatment effect estimation, interference modeling, and emulation techniques that accelerate policy evaluation
Build and maintain production-grade experimentation infrastructure and analytical tools using Python, SQL, Scala, and related technologies
Perform large-scale exploratory data analysis to uncover patterns, identify opportunities, and inform experimental design and policy development
Develop and scale supply chain emulation systems that model inventory dynamics end to end, enabling rapid offline evaluation of policy changes across millions of products without the cost and latency of live experiments
Translate complex research findings into clear insights and recommendations for technical and non-technical stakeholders at all levels
Contribute to Amazon's scientific community and the broader research field through collaboration and publication in top-tier venues
You might start the morning reviewing results from a randomized controlled trial running across millions of products, digging into causal estimates and designing the next iteration. Later, you could be designing an experiment with a partner team where interference is unavoidable: treated and control units share fulfillment networks and inventory pools, and you need a credible strategy despite the spillover effects.
You'll build supply chain emulation systems that replicate inventory dynamics end to end, write code in Python, Scala, and SQL at a scale most scientists never encounter, and collaborate with scientists, engineers, and business teams across SCOT. Your research has a real chance of being published at top venues.
The work is hard, the problems are unsolved, and the impact is immediate. If you want to do research that ships, this is where you do it.

View full posting on CareerOneStop → ID: c5de427b9901

Data Scientist, Labs, SCOT Forecasting and Labs

Amazon · Bellevue, WA

Mid-level Doctorate

2026-04-25

WA 2026-04-25

Requirements

3+ years of machine learning, statistical modeling, data mining, and analytics techniques experience
3+ years of data querying languages (e.g. SQL), scripting languages (e.g. Python) or statistical/mathematical software (e.g. R, SAS, Matlab, etc.) experience
3+ years of data scientist experience
Bachelor's degree

Preferred

Master's degree, or PhD
Natural curiosity and desire to learn

Responsibilities

Partner with customer teams to design rigorous large-scale experiments (such as randomized controlled trials and quasi-experiments) to evaluate policy updates and model improvements across millions of products, hundreds of fulfillment nodes, and diverse business contexts
Lead the end-to-end experimentation lifecycle, from hypothesis formulation through analysis and stakeholder alignment, to inform production rollout decisions
Advance causal inference methodology for supply chain settings, including treatment effect estimation, interference modeling, and emulation techniques that accelerate policy evaluation
Build and maintain production-grade experimentation infrastructure and analytical tools using Python, SQL, Scala, and related technologies
Perform large-scale exploratory data analysis to uncover patterns, identify opportunities, and inform experimental design and policy development
Develop and scale supply chain emulation systems that model inventory dynamics end to end, enabling rapid offline evaluation of policy changes across millions of products without the cost and latency of live experiments
Translate complex research findings into clear insights and recommendations for technical and non-technical stakeholders at all levels
Contribute to Amazon's scientific community and the broader research field through collaboration and publication in top-tier venues
You might start the morning reviewing results from a randomized controlled trial running across millions of products, digging into causal estimates and designing the next iteration. Later, you could be designing an experiment with a partner team where interference is unavoidable: treated and control units share fulfillment networks and inventory pools, and you need a credible strategy despite the spillover effects.
You'll build supply chain emulation systems that replicate inventory dynamics end to end, write code in Python, Scala, and SQL at a scale most scientists never encounter, and collaborate with scientists, engineers, and business teams across SCOT. Your research has a real chance of being published at top venues.
The work is hard, the problems are unsolved, and the impact is immediate. If you want to do research that ships, this is where you do it.

View full posting on CareerOneStop → ID: 32120793dbf4

Data Scientist, SPX AI Lab, SPX Science

Amazon · Seattle, WA

Mid-level Master's

2026-04-25

WA 2026-04-25

Requirements

2+ years of data scientist experience
3+ years of data querying languages (e.g. SQL), scripting languages (e.g. Python) or statistical/mathematical software (e.g. R, SAS, Matlab, etc.) experience
3+ years of machine learning/statistical modeling data analysis tools and techniques, and parameters that affect their performance experience
1+ years of working with or evaluating AI systems experience
Master's degree in Science, Technology, Engineering, or Mathematics (STEM), or experience working in Science, Technology, Engineering, or Mathematics (STEM)

Preferred

Knowledge of machine learning concepts and their application to reasoning and problem-solving
Experience in a ML or data scientist role with a large technology company
Experience in defining and creating benchmarks for assessing GenAI model performance
Experience working on multi-team, cross-disciplinary projects
Experience applying quantitative analysis to solve business problems and making data-driven business decisions
Experience effectively communicating complex concepts through written and verbal communication

Responsibilities

- Respond to Seller feedback and implement fix in Gen AI solution to enhance Seller experience
- Drive deep-dive analytical studies to understand seller pain points, evaluate feature performance, and identify opportunities to improve the Selling Partner experience.
- Design and execute robust causal inference and measurement frameworks, including A/B testing, quasi-experiments, and observational causal methods (e.g., diff-in-diff, synthetic control, propensity score methods).
- Develop scalable analytical pipelines for impact measurement, KPI development, metric integrity validation, and long-term business monitoring.
- Apply NLP and statistical modeling techniques-including topic modeling, clustering, semantic similarity, and classification-to uncover insights from unstructured seller interactions, feedback, and content.
- Partner with scientists, engineers, economists, and product managers to translate ambiguous problems into structured analytical approaches and influence product roadmaps with data-driven recommendations.
- Build and maintain automated analytics tools and dashboards to democratize insights for product, science, and engineering teams.
- Collaborate scientists to evaluate model-driven features, quantify impact, and ensure mechanisms are grounded in rigorous measurement.
- Research and experiment with new analytical and measurement methodologies, ensuring Amazon leverages the latest best practices in causal inference, NLP, and GenAI.

View full posting on CareerOneStop → ID: c879768837cc

Data Scientist, SPX AI Lab, SPX Science

Amazon · Seattle, WA

Mid-level Master's

2026-04-25

WA 2026-04-25

Requirements

2+ years of data scientist experience
3+ years of data querying languages (e.g. SQL), scripting languages (e.g. Python) or statistical/mathematical software (e.g. R, SAS, Matlab, etc.) experience
3+ years of machine learning/statistical modeling data analysis tools and techniques, and parameters that affect their performance experience
1+ years of working with or evaluating AI systems experience
Master's degree in Science, Technology, Engineering, or Mathematics (STEM), or experience working in Science, Technology, Engineering, or Mathematics (STEM)

Preferred

Knowledge of machine learning concepts and their application to reasoning and problem-solving
Experience in a ML or data scientist role with a large technology company
Experience in defining and creating benchmarks for assessing GenAI model performance
Experience working on multi-team, cross-disciplinary projects
Experience applying quantitative analysis to solve business problems and making data-driven business decisions
Experience effectively communicating complex concepts through written and verbal communication

Responsibilities

- Respond to Seller feedback and implement fix in Gen AI solution to enhance Seller experience
- Drive deep-dive analytical studies to understand seller pain points, evaluate feature performance, and identify opportunities to improve the Selling Partner experience.
- Design and execute robust causal inference and measurement frameworks, including A/B testing, quasi-experiments, and observational causal methods (e.g., diff-in-diff, synthetic control, propensity score methods).
- Develop scalable analytical pipelines for impact measurement, KPI development, metric integrity validation, and long-term business monitoring.
- Apply NLP and statistical modeling techniques-including topic modeling, clustering, semantic similarity, and classification-to uncover insights from unstructured seller interactions, feedback, and content.
- Partner with scientists, engineers, economists, and product managers to translate ambiguous problems into structured analytical approaches and influence product roadmaps with data-driven recommendations.
- Build and maintain automated analytics tools and dashboards to democratize insights for product, science, and engineering teams.
- Collaborate scientists to evaluate model-driven features, quantify impact, and ensure mechanisms are grounded in rigorous measurement.
- Research and experiment with new analytical and measurement methodologies, ensuring Amazon leverages the latest best practices in causal inference, NLP, and GenAI.

View full posting on CareerOneStop → ID: 0bf2d38bf5af

Data Scientist, SPX AI Lab, SPX Science

Amazon · Seattle, WA

Mid-level Master's

2026-04-25

WA 2026-04-25

Requirements

2+ years of data scientist experience
3+ years of data querying languages (e.g. SQL), scripting languages (e.g. Python) or statistical/mathematical software (e.g. R, SAS, Matlab, etc.) experience
3+ years of machine learning/statistical modeling data analysis tools and techniques, and parameters that affect their performance experience
1+ years of working with or evaluating AI systems experience
Master's degree in Science, Technology, Engineering, or Mathematics (STEM), or experience working in Science, Technology, Engineering, or Mathematics (STEM)

Preferred

Knowledge of machine learning concepts and their application to reasoning and problem-solving
Experience in a ML or data scientist role with a large technology company
Experience in defining and creating benchmarks for assessing GenAI model performance
Experience working on multi-team, cross-disciplinary projects
Experience applying quantitative analysis to solve business problems and making data-driven business decisions
Experience effectively communicating complex concepts through written and verbal communication

Responsibilities

- Respond to Seller feedback and implement fix in Gen AI solution to enhance Seller experience
- Drive deep-dive analytical studies to understand seller pain points, evaluate feature performance, and identify opportunities to improve the Selling Partner experience.
- Design and execute robust causal inference and measurement frameworks, including A/B testing, quasi-experiments, and observational causal methods (e.g., diff-in-diff, synthetic control, propensity score methods).
- Develop scalable analytical pipelines for impact measurement, KPI development, metric integrity validation, and long-term business monitoring.
- Apply NLP and statistical modeling techniques-including topic modeling, clustering, semantic similarity, and classification-to uncover insights from unstructured seller interactions, feedback, and content.
- Partner with scientists, engineers, economists, and product managers to translate ambiguous problems into structured analytical approaches and influence product roadmaps with data-driven recommendations.
- Build and maintain automated analytics tools and dashboards to democratize insights for product, science, and engineering teams.
- Collaborate scientists to evaluate model-driven features, quantify impact, and ensure mechanisms are grounded in rigorous measurement.
- Research and experiment with new analytical and measurement methodologies, ensuring Amazon leverages the latest best practices in causal inference, NLP, and GenAI.

View full posting on CareerOneStop → ID: 6c6c5b5d3d9b

Software Dev Engineer, EC2 Nitro, EC2 Nitro Machine Learning Systems

Amazon · Seattle, WA

Mid-level Bachelor's

2026-04-25

WA 2026-04-25

Requirements

3+ years of non-internship professional software development experience
2+ years of non-internship design or architecture (design patterns, reliability and scaling) of new and existing systems experience
Bachelor's degree or foreign equivalent in Computer Science, Engineering, Mathematics, or a related field
Experience programming with at least one software programming language
1+ years of designing and developing large-scale, multi-tiered, multi-threaded, embedded software applications, tools, systems, and services using: C, C++, Rust in Linux environment
1+ years of embedded software development experience

Preferred

3+ years of full software development life cycle, including coding standards, code reviews, source control management, build processes, testing, and operations experience
Bachelor's degree in computer science or equivalent

View full posting on CareerOneStop → ID: 2e08760626ec

Data Scientist II - AI Assurance Researcher

Pacific Northwest National Laboratory · Richland, WA

Mid-level Doctorate

2026-04-25

WA 2026-04-25

Requirements

BS/BA and 2 years of relevant experience -OR-
U.S. Citizenship
Background Investigation: Applicants selected will be subject to a Federal background investigation and must meet eligibility requirements for access to classified matter in accordance with 10 CFR 710, Appendix B.
As a national laboratory, PNNL is responsible for adhering to the Homeland Security Presidential Directive 12 (HSPD-12) and Department of Energy (DOE) Order 473.1A, which require new employees to obtain and maintain a HSPD-12 Personal Identify Verification (PIV) Credential. To obtain this credential, new employees must successfully complete the applicable tier of federal background investigation post hire and receive a favorable federal adjudication. The tier of federal background investigation will be determined by job duties and national security or public trust responsibilities associated with the job. All tiers of investigation include a declaration of illegal drug activities, including use, supply, possession, or manufacture within the last 1 to 7 years (depending on the applicable tier of investigation). Illegal drug activities include marijuana and cannabis derivatives, which are still considered illegal under federal law, regardless of state laws.
For foreign national candidates:
If you have not resided in the U.S. for three consecutive years, you are not eligible for the PIV credential and instead will need to obtain a favorable Local Site Specific Only (LSSO) Federal risk determination to maintain employment. Once you meet the three-year residency requirement thereafter, you will be required to obtain a PIV credential to maintain employment. The tier of federal background investigation required to obtain the PIV credential will be determined by job duties at the time you become eligible for the PIV credential.
Please be aware that the Department of Energy (DOE) prohibits DOE employees and contractors from having any affiliation with the foreign government of a country DOE has identified as a "country of risk" without explicit approval by DOE and Battelle. If you are offered a position at PNNL and currently have any affiliation with the government of one of these countries, you will be required to disclose this information and recuse yourself of that affiliation or receive approval from DOE and Battelle prior to your first day of employment.
*Rockstar Rewards

Preferred

Degree in computer science, engineering, mathematics, or a related field.
Familiarity with the current ML research landscape, particularly in explainable AI, adversarial machine learning, AI safety, and the science of deep learning.
Hands-on experience analyzing the internal structures of deep learning models, particularly large language models and large vision models.
Proficiency in PyTorch and associated deep learning libraries.
Experience designing and executing experiments on HPC systems.
Experience in translating research prototypes into deployable tools and capabilities.
Demonstrated strong communication and collaboration skills, with the ability to work effectively in a multi-disciplinary team environment.

Responsibilities

PNNL is seeking a Data Scientist II - AI Assurance Researcher who has experience in understanding, exploring, and manipulating the internal mechanics and behaviors of AI models and can provide valuable insights into the decision boundaries and mathematical fingerprints of data properties. The selected candidate should have extensive experience training models, accessing and working with data embeddings, the ability to derive theoretical queries from empirical results, and demonstrate the capacity to translate research papers and findings into mission relevant insights and tools.
Designs and executes rigorous ML experiments following community best practices, including large-scale training and evaluation on HPC infrastructure.
Evaluates AI systems across multiple dimensions, including standard performance metrics, generalization, robustness, and out-of-distribution behavior.
Analyzes the internal structures and representations of deep learning models, with emphasis on large language models and large vision models.
Assesses empirical results to identify trends, inform research direction, and recommend next steps.
Writes high-quality, well-documented research code that supports reproducibility and collaboration.
Contributes to publications and technical reports that communicate findings to both internal and external audiences.
Collaborates with senior researchers, engineers, and cross-functional teams to integrate research into broader systems and workflows.
Conducts work in secure environments with adherence to operational security requirements.
*This position is based in either Richland, WA or Seattle, WA and requires an onsite presence.

View full posting on CareerOneStop → ID: 0c61ba8edab7

Data Scientist

PLURALSIGHT, LLC · Draper, UT

Mid-level

2026-04-25

UT 2026-04-25

View full posting on CareerOneStop → ID: 08f19a4d100c

AI/ML Engineer II

USAA · Phoenix, AZ

Mid-level

2026-04-25

AZ 2026-04-25

View full posting on CareerOneStop → ID: 76e67fa1e59d

Business Data Scientist, Marketing Analytics

BECU · Seattle, WA

Mid-level

2026-04-24

WA 2026-04-24

Responsibilities

*Partner with Marketing to Define and Solve Problems - Work closely with marketing stakeholders to understand business challenges, define success metrics, and translate needs into analytical approaches that drive performance across campaigns and channels.
*Design and Deliver Data-Driven Solutions - Apply statistical analysis and machine learning to develop solutions that address business needs, then present findings, influence decisions, and gain alignment on adoption.
*Lead Experimentation and Optimization - Develop and manage testing frameworks (A/B testing, campaign experimentation) across channels and markets. Analyze results and provide clear recommendations to improve performance and inform future strategy.
*Translate Results into Business Impact - Clearly communicate insights and quantify outcomes (e.g., campaign performance lift, engagement improvements, ROI) to ensure stakeholders understand the value and

View full posting on CareerOneStop → ID: 5cae691f93c2

Machine Learning Engineer

Indeed · Seattle, WA

Mid-level Master's

2026-04-23

WA 2026-04-23

Responsibilities

The Machine Learning Engineer I role partners closely with business partners across various functions to help execute strategic initiatives that increase revenue, drive operational scale, and improve efficiency for continuous growth. As a Machine Learning Engineer, you will prepare datasets, train and optimize models, and maintain and improve model inference services. You will learn and apply new techniques from open source packages and research publications, and creatively adapt models for solving business problems across Indeed.
Work spans classical ML through LLM systems. You improve search and retrieval quality using real user signals. Execution includes experiments, iteration, and production reliability at scale. You collaborate with engineers, data scientists, and product teams to define problems, test approaches, and ship measurable improvements.
Build AI/ML systems for search, ranking, and recommendations
Develop LLM retrieval and generation workflows
Improve search and ranking relevance
Design metrics and run experiments
Monitor model quality, latency, and cost
Debug data, models, and system issues
Build training, inference, and eval pipelines
*Skills/Competencies
Requires a Bachelor's degree in Computer Science, Mathematics, or Statistics, and a minimum of 2 years of related experience; or an advanced degree without experience
Experience building ML models in Python; solid software engineering and algorithms fundamentals
Experience developing backend services in Java/Kotlin for ML-driven systems and features
Experience writing clean, testable, and maintainable production code
Experience working with structured and unstructured data, including SQL for large-scale data querying, and building scalable data pipelines and features from data
Experience integrating ML models into search systems using engines such as OpenSearch or similar, with familiarity in container orchestration for deployment with senior guidance
Excellent understanding of model evaluation techniques, feature engineering, experiment design, and familiarity with LLM systems (RAG, embeddings, output evaluation)

View full posting on CareerOneStop → ID: 8e3fc20531d1

Machine Learning Engineer

Indeed · Portland, OR

Mid-level Master's

2026-04-23

WA 2026-04-23

Responsibilities

The Machine Learning Engineer I role partners closely with business partners across various functions to help execute strategic initiatives that increase revenue, drive operational scale, and improve efficiency for continuous growth. As a Machine Learning Engineer, you will prepare datasets, train and optimize models, and maintain and improve model inference services. You will learn and apply new techniques from open source packages and research publications, and creatively adapt models for solving business problems across Indeed.
Work spans classical ML through LLM systems. You improve search and retrieval quality using real user signals. Execution includes experiments, iteration, and production reliability at scale. You collaborate with engineers, data scientists, and product teams to define problems, test approaches, and ship measurable improvements.
Build AI/ML systems for search, ranking, and recommendations
Develop LLM retrieval and generation workflows
Improve search and ranking relevance
Design metrics and run experiments
Monitor model quality, latency, and cost
Debug data, models, and system issues
Build training, inference, and eval pipelines
*Skills/Competencies
Requires a Bachelor's degree in Computer Science, Mathematics, or Statistics, and a minimum of 2 years of related experience; or an advanced degree without experience
Experience building ML models in Python; solid software engineering and algorithms fundamentals
Experience developing backend services in Java/Kotlin for ML-driven systems and features
Experience writing clean, testable, and maintainable production code
Experience working with structured and unstructured data, including SQL for large-scale data querying, and building scalable data pipelines and features from data
Experience integrating ML models into search systems using engines such as OpenSearch or similar, with familiarity in container orchestration for deployment with senior guidance
Excellent understanding of model evaluation techniques, feature engineering, experiment design, and familiarity with LLM systems (RAG, embeddings, output evaluation)

View full posting on CareerOneStop → ID: 798a789e964a

Machine Learning Engineer

Indeed · Boise, ID

Mid-level

2026-04-23

ID 2026-04-23

View full posting on CareerOneStop → ID: 1ea1ccdbe7c3

Machine Learning Engineer

Indeed · Helena, MT

Mid-level

2026-04-23

MT 2026-04-23

View full posting on CareerOneStop → ID: 3533ec2c9f2f

Machine Learning Engineer

Indeed · Cheyenne, WY

Mid-level

2026-04-23

WY 2026-04-23

View full posting on CareerOneStop → ID: 87b5cd3ef4f9

Machine Learning Engineer

Indeed · Salt Lake City, UT

Mid-level

2026-04-23

UT 2026-04-23

View full posting on CareerOneStop → ID: 8f12b4b4ebdd

Machine Learning Engineer

Indeed · Las Vegas, NV

Mid-level

2026-04-23

NV 2026-04-23

View full posting on CareerOneStop → ID: 3d915a3b0830

Machine Learning Engineer

Indeed · Bismarck, ND

Mid-level

2026-04-23

ND 2026-04-23

View full posting on CareerOneStop → ID: f99c11ec59f8

Machine Learning Engineer

Indeed · Sioux Falls, SD

Mid-level

2026-04-23

SD 2026-04-23

View full posting on CareerOneStop → ID: e5080e1bd243

Machine Learning Engineer

Indeed · Albuquerque, NM

Mid-level

2026-04-23

NM 2026-04-23

View full posting on CareerOneStop → ID: 911eed7fe60c

Machine Learning Engineer

Indeed · Omaha, NE

Mid-level

2026-04-23

NE 2026-04-23

View full posting on CareerOneStop → ID: 2b0ea217ace1

Machine Learning Engineer

Indeed · Kansas City, KS

Mid-level

2026-04-23

KS 2026-04-23

View full posting on CareerOneStop → ID: 1ed93043eaa8

Machine Learning Engineer

Indeed · Oklahoma City, OK

Mid-level

2026-04-23

OK 2026-04-23

View full posting on CareerOneStop → ID: 6801b18b8bad

Machine Learning Engineer

Indeed · Des Moines, IA

Mid-level

2026-04-23

IA 2026-04-23

View full posting on CareerOneStop → ID: ac9a36717f79

Machine Learning Engineer

Indeed · Saint Louis, MO

Mid-level

2026-04-23

MO 2026-04-23

View full posting on CareerOneStop → ID: 4d67deffd062

Machine Learning Engineer

Indeed · Little Rock, AR

Mid-level

2026-04-23

AR 2026-04-23

View full posting on CareerOneStop → ID: d94fddee36ad

Machine Learning Engineer

Indeed · Baton Rouge, LA

Mid-level

2026-04-23

LA 2026-04-23

View full posting on CareerOneStop → ID: 325e5c4bab69

Machine Learning Engineer

Indeed · Jackson, MS

Mid-level

2026-04-23

MS 2026-04-23

View full posting on CareerOneStop → ID: 13401d7322b3

Machine Learning Engineer

Indeed · Huntsville, AL

Mid-level

2026-04-23

AL 2026-04-23

View full posting on CareerOneStop → ID: 166be97e2d08

Machine Learning Engineer

Indeed · Louisville, KY

Mid-level

2026-04-23

KY 2026-04-23

View full posting on CareerOneStop → ID: c4008c409387

Data Scientist III - AMZ9971313

Amazon · Seattle, WA

Mid-level Master's

2026-04-22

WA 2026-04-22

Preferred

Please see job description and the position requirements above.

Responsibilities

Own the data science elements of various products to help with data-based decision making, product performance optimization, and product performance tracking. Work directly with product managers to help drive the design of the product. Work with Technical Product Managers to help drive the build planning. Translate business problems and products into data requirements and metrics. Initiate the design, development, and implementation of scientific analysis projects or deliverables. Own the analysis, modelling, system design, and development of data science solutions for products. Write documents and make presentations that explain model/analysis results to the business. Bridge the degree of uncertainty in both problem definition and data scientific solution approaches. Build consensus on data, metrics, and analysis to drive business and system strategy.
40 hours / week, 8:00am-5:00pm, Salary Range $165,006/year to $215,300/year.
Amazon is a total compensation company. Dependent on the position offered, equity, sign-on payments, and other forms of compensation may be provided as part of a total compensation package, in addition to a full range of medical, financial, and/or other benefits. For more information, visit:

View full posting on CareerOneStop → ID: fcdf242c6404

Machine Learning Engineer, (Applied Machine Learning), AI & Data Platforms (AiDP)

Apple · Seattle, WA

Mid-level Doctorate

2026-04-22

WA 2026-04-22

Requirements

Bachelor of Science in Computer Science, Machine Learning, or a related quantitative field or equivalent experience
2+ years of hands-on experience in applied AI/machine learning work in industry or 4+ years of hands on AI research and development experience in academia
Demonstrated expertise in generative AI, computer vision, natural language processing, or general machine learning with a passion for problem solving.

Preferred

MS or Phd in Machine Learning, Natural Language Processing, Computer Vision or related areas strongly preferred
Experience in ML frameworks for training, fine-tuning, and deploying ML/generative models at scale
Proven track record of building large scale, enterprise-grade ML/Gen-AI products in cloud environments (AWS, GCP , Azure) or on-prem infrastructure

Responsibilities

Imagine what you could do here. At Apple, revolutionary ideas have a way of becoming extraordinary products, services, and customer experiences. Join the Ai Data Platform Applied Machine Learning team to pioneer enterprise solutions where generative AI meets Apple's unique commitment to privacy-first innovation. Together, we'll create tools that redefine industries while safeguarding what matters most - our users' trust.
As a pivotal member of Apple's enterprise generative AI efforts, you will help design, build, and evolve models, tools and applications that power high-impact AI experiences across the company. You will contribute to the architecture and optimization of AI/gen AI systems built for high availability, scalability, and reliability, working across backend services and application layers. You would solve AI problems in gen AI Safety, machine translation, content understanding, multi-modality, multi-agent systems, fine tuning and more. Our team designs and implements SOTA AI Models, services, and AI platform components that advance adoption of gen AI at apple. We tackle unique AI challenges in AI Safety, privacy-preserving generations, efficient inference, and multimodal integration, while enabling teams to build on top of our foundations. We deliver production-grade systems and models that meet Apple's rigorous standards for quality, performance, and scalability.

View full posting on CareerOneStop → ID: 41a389766942

ML Engineer - Automated Evaluation and Adversarial Design

Apple · Seattle, WA

Mid-level Master's

2026-04-22

WA 2026-04-22

Requirements

Bachelor's degree in Computer Science, Machine Learning, Statistics, or a related field
4+ years of experience building or significantly extending ML evaluation systems, including designing evaluation benchmarks or quality assessment frameworks including evaluation of sequential or multi-step AI outputs
Experience independently defining evaluation architecture and methodology for AI or ML systems with the ability to design evaluation approaches where the unit of analysis is a conversation or session rather than a single output
Experience designing adversarial or red-teaming test methodologies for ML models or AI-powered features including adversarial scenarios that target failures across multi-turn interactions
Experience with Python and ML frameworks (PyTorch, TensorFlow, or equivalent) in production or near-production settings
Track record of owning technical direction for evaluation efforts across multiple features or product areas

Preferred

Experience evaluating user-facing AI features in consumer applications, with an understanding of how technical metrics connect to user-perceived quality
Familiarity with productivity software or creative tools, with the ability to assess output quality from a user workflow perspective
Experience ensuring alignment between automated and human evaluation methods, including inter-annotator agreement analysis and bias detection
Track record of designing evaluation systems that scale across multiple features or product areas without requiring bespoke solutions for each
Experience evaluating different types of AI systems, including API-based and custom-trained models
Demonstrated ability to communicate evaluation findings and readiness assessments to cross-functional partners
Experience leveraging automation to scale evaluation data generation and analysis
Experience building evaluation pipelines for conversational AI, dialogue systems, or agentic workflows, including turn-level and session-level automated scoring
Familiarity with agent orchestration frameworks (LangChain, LangGraph, CrewAI, AutoGen) and observability tooling (LangSmith, Braintrust, Arize), with an understanding of how to instrument and evaluate multi-step agent runs
Experience designing adversarial tests for tool-use reliability, function-calling accuracy, or agent planning quality
Graduate degree in a relevant field

Responsibilities

The Productivity and Machine Learning Evaluation team ensures the quality of AI-powered features across a suite of productivity and creative applications; including Creator Studio, used by hundreds of millions of people. This team serves as the primary evaluation function, providing critical quality signals that directly influence model development decisions and product launches.
This role focuses on building and scaling automated evaluation systems and designing adversarial and stress-testing methodologies across multiple AI features. The work requires a deep understanding of how AI systems fail and how to measure quality rigorously. As features evolve from single-turn interactions into multi-turn, agentic experiences, the evaluation challenge shifts from assessing individual outputs to stress-testing entire conversation flows and agent decision chains. This is an opportunity to shape the evaluation infrastructure that determines whether AI features meet the bar for hundreds of millions of users.
Day-to-day work involves designing, building, and maintaining automated evaluation systems that assess AI feature quality at scale, including multi-turn conversation evaluation and end-to-end agent workflow testing. This includes creating adversarial test suites that probe model weaknesses and running stress tests to ensure features perform under demanding conditions, with particular focus on failure modes that only emerge across extended interactions, such as: context degradation, goal drift, and compounding errors.
Typical deliverables include: evaluation frameworks and rubrics, quality assessment reports, adversarial test case libraries, multi-turn stress-test pipelines, and recommendations on model readiness.

View full posting on CareerOneStop → ID: 3c394469498c

ML Engineer - Evaluation Analysis, Metric and Data Strategy

Apple · Seattle, WA

Mid-level Master's

2026-04-22

WA 2026-04-22

Requirements

Bachelor's degree in Statistics, Data Science, Applied Mathematics, Computer Science, or a related quantitative field
5+ years of experience in applied science, data science, or evaluation research, with a focus on defining and operationalizing quality metrics
Experience with statistical analysis methods including significance testing, sampling design, effect size estimation, and experimental design
Experience working with production user data, understanding its biases and limitations compared to controlled evaluation data, including familiarity with sequential interaction data where context and turn order affect quality assessment
Ability to design evaluation approaches where the unit of analysis is a session or conversation rather than a single model output
Track record of independently designing metrics frameworks and driving data-informed decisions across cross-functional teams
Proficiency in Python (pandas, scipy, scikit-learn) or R for data analysis and visualization

Preferred

Experience designing evaluation or quality metrics for AI-powered or ML-driven features in consumer-facing products
Familiarity with productivity software or creative applications, with an ability to distinguish between technically correct and genuinely useful AI outputs
Experience partnering with engineering or data teams to define data collection requirements and schemas
Track record of translating complex analytical findings into concise recommendations for non-technical decision-makers
Experience evaluating tool-use accuracy, retrieval quality, or function-calling reliability within AI systems
Experience with evaluation methodology including inter-annotator agreement, evaluation bias detection, and dataset representativeness auditing
Familiarity with agentic orchestration frameworks (LangChain, LangGraph, CrewAI, AutoGen) and emerging agent interoperability protocols (A2A, MCP), with an understanding of how architectural choices in agent design affect evaluability
Understanding of ML model development processes, with the ability to specify what evaluation signals are useful for model improvement
Experience managing evaluation across multiple features or product areas simultaneously, with systematic rather than ad-hoc approaches
Graduate degree in a relevant quantitative field

Responsibilities

The Productivity and Machine Learning Evaluation team ensures the quality of AI-powered features across a suite of productivity and creative applications; including Creator Studio, used by hundreds of millions of people. This team serves as the primary evaluation function, and its analysis directly informs decisions about model development, feature launches, and product direction.
This role is the analytical core of the team; responsible for making sense of evaluation signals and real-world user behavior. The work involves designing feature-level quality metrics, collaborating with partner teams on data collection strategies, and translating evaluation data into concise, actionable insights that drive decisions. This is an opportunity to define how AI feature quality is measured and to directly shape what gets shipped. As AI features evolve into multi-turn, agentic experiences, this role will define what "quality" means when the unit of evaluation is a conversation, not a single response.
Day-to-day work involves analyzing evaluation results, identifying trends, regressions, and segment-level patterns across multiple AI features. This includes collaborating with partner teams on data collection strategies, ensuring evaluation data is representative of real-world usage, and designing the metrics framework that leadership uses to make decisions on AI features.
Typical deliverables include: feature-level quality metrics and dashboards, evaluation analysis reports, data collection requirements, dataset representativeness audits, multi-turn evaluation frameworks and session-level scoring rubrics, and concise metric summaries for decision-makers.

View full posting on CareerOneStop → ID: bb191e99c6a9

DATA SCIENTIST

State of Arkansas · Little Rock, AR

Mid-level

2026-04-22

AR 2026-04-22

View full posting on CareerOneStop → ID: fa846a23f9d3

Data Scientist II, Amazon Stores Finance Science

Amazon · Bellevue, WA

Mid-level Master's

2026-04-21

WA 2026-04-21

Requirements

2+ years of data scientist experience
3+ years of data querying languages (e.g. SQL), scripting languages (e.g. Python) or statistical/mathematical software (e.g. R, SAS, Matlab, etc.) experience
3+ years of machine learning/statistical modeling data analysis tools and techniques, and parameters that affect their performance experience
Experience applying theoretical models in an applied environment
Bachelor's degree

Preferred

Experience in a ML or data scientist role with a large technology company
Experience working on multi-team, cross-disciplinary projects
Experience effectively communicating complex concepts through written and verbal communication
Master's degree
Experience formulating and solving predictive modeling, machine learning, forecasting or statistical modeling problems

Responsibilities

Demonstrating thorough technical knowledge, effective exploratory data analysis, and model building using industry standard ML models
Working with technical and non-technical stakeholders across every step of science project life cycle
Collaborating with finance, product, data engineering, and software engineering teams to create production implementations for large-scale ML models
Innovating by adapting new modeling techniques and procedures
Presenting research results to our internal research community

View full posting on CareerOneStop → ID: 1e66715e63dc

Product Test Engineer - Machine Learning Hardware, RRL Technical Engineering, RRL Technical Engineering

Amazon · Florence, KY

Mid-level

2026-04-21

KY 2026-04-21

View full posting on CareerOneStop → ID: 73827fd56bcb

Machine Learning Engineer

Indeed · Portland, OR

Mid-level Master's

2026-04-16

WA 2026-04-16

Responsibilities

The Machine Learning Engineer I role partners closely with business partners across various functions to help execute strategic initiatives that increase revenue, drive operational scale, and improve efficiency for continuous growth. As a Machine Learning Engineer, you will prepare datasets, train and optimize models, and maintain and improve model inference services. You will learn and apply new techniques from open source packages and research publications, and creatively adapt models for solving business problems across Indeed.
Work spans classical ML through LLM systems. You improve search and retrieval quality using real user signals. Execution includes experiments, iteration, and production reliability at scale. You collaborate with engineers, data scientists, and product teams to define problems, test approaches, and ship measurable improvements.
Build AI/ML systems for search, ranking, and recommendations
Develop LLM retrieval and generation workflows
Improve search and ranking relevance
Design metrics and run experiments
Monitor model quality, latency, and cost
Debug data, models, and system issues
Build training, inference, and eval pipelines
*Skills/Competencies
Requires a Bachelor's degree in Computer Science, Mathematics, or Statistics, and a minimum of 2 years of related experience; or an advanced degree without experience
Experience building ML models in Python; solid software engineering and algorithms fundamentals
Experience developing backend services in Java/Kotlin for ML-driven systems and features
Experience writing clean, testable, and maintainable production code
Experience working with structured and unstructured data, including SQL for large-scale data querying, and building scalable data pipelines and features from data
Experience integrating ML models into search systems using engines such as OpenSearch or similar, with familiarity in container orchestration for deployment with senior guidance
Excellent understanding of model evaluation techniques, feature engineering, experiment design, and familiarity with LLM systems (RAG, embeddings, output evaluation)

View full posting on CareerOneStop → ID: d701d3f0cddb

Machine Learning Engineer

Indeed · Boise, ID

Mid-level

2026-04-16

ID 2026-04-16

View full posting on CareerOneStop → ID: 726d72daf191

Machine Learning Engineer

Indeed · Helena, MT

Mid-level

2026-04-16

MT 2026-04-16

View full posting on CareerOneStop → ID: c74d033d23de

Machine Learning Engineer

Indeed · Cheyenne, WY

Mid-level

2026-04-16

WY 2026-04-16

View full posting on CareerOneStop → ID: 4851d2e89227

Machine Learning Engineer

Indeed · Las Vegas, NV

Mid-level

2026-04-16

NV 2026-04-16

View full posting on CareerOneStop → ID: 2f62e69214a8

Machine Learning Engineer

Indeed · Bismarck, ND

Mid-level

2026-04-16

ND 2026-04-16

View full posting on CareerOneStop → ID: 536de2c96ad8

Machine Learning Engineer

Indeed · Sioux Falls, SD

Mid-level

2026-04-16

SD 2026-04-16

View full posting on CareerOneStop → ID: 37b55b9d5b9b

Machine Learning Engineer

Indeed · Albuquerque, NM

Mid-level

2026-04-16

NM 2026-04-16

View full posting on CareerOneStop → ID: 4e75a8e26fb2

Machine Learning Engineer

Indeed · Omaha, NE

Mid-level

2026-04-16

NE 2026-04-16

View full posting on CareerOneStop → ID: 36ed73aab38a

Machine Learning Engineer

Indeed · Kansas City, KS

Mid-level

2026-04-16

KS 2026-04-16

View full posting on CareerOneStop → ID: cb7b5340e364

Machine Learning Engineer

Indeed · Oklahoma City, OK

Mid-level

2026-04-16

OK 2026-04-16

View full posting on CareerOneStop → ID: 9d992ad35aad

Machine Learning Engineer

Indeed · Des Moines, IA

Mid-level

2026-04-16

IA 2026-04-16

View full posting on CareerOneStop → ID: 0d08f3956d40

Data Scientist

Arkansas Employer · Little Rock, AR

Mid-level

2026-04-16

AR 2026-04-16

View full posting on CareerOneStop → ID: 644fed4e1271

Machine Learning Engineer

Indeed · Little Rock, AR

Mid-level

2026-04-16

AR 2026-04-16

View full posting on CareerOneStop → ID: a4ba4396f97f

Machine Learning Engineer

Indeed · Baton Rouge, LA

Mid-level

2026-04-16

LA 2026-04-16

View full posting on CareerOneStop → ID: e472d7d36246

Machine Learning Engineer

Indeed · Jackson, MS

Mid-level

2026-04-16

MS 2026-04-16

View full posting on CareerOneStop → ID: 10894189e6d9

Machine Learning Engineer

Indeed · Huntsville, AL

Mid-level

2026-04-16

AL 2026-04-16

View full posting on CareerOneStop → ID: 2e06bb1e0425

Machine Learning Engineer

Indeed · Louisville, KY

Mid-level

2026-04-16

KY 2026-04-16

View full posting on CareerOneStop → ID: 196d7e0f8820

Data Scientist (5190)

SMX · Olympia, WA

Mid-level

2026-04-09

WA 2026-04-09

View full posting on CareerOneStop → ID: 971cb7d256a5

Data Scientist (5190)

SMX · Boise, ID

Mid-level

2026-04-09

ID 2026-04-09

View full posting on CareerOneStop → ID: 490e261ca5f6

Data Scientist (5190)

SMX · Salem, OR

Mid-level

2026-04-09

OR 2026-04-09

View full posting on CareerOneStop → ID: e0b698b05c94

Data Scientist (5190)

SMX · Helena, MT

Mid-level

2026-04-09

MT 2026-04-09

View full posting on CareerOneStop → ID: 19a9ba327f86

Data Scientist (5190)

SMX · Cheyenne, WY

Mid-level

2026-04-09

WY 2026-04-09

View full posting on CareerOneStop → ID: 5d2c8beb3642

Data Scientist (5190)

SMX · Carson City, NV

Mid-level

2026-04-09

NV 2026-04-09

View full posting on CareerOneStop → ID: 111702713c06

Data Scientist (5190)

SMX · Bismarck, ND

Mid-level

2026-04-09

ND 2026-04-09

View full posting on CareerOneStop → ID: 5cc7ce271681

Data Scientist (5190)

SMX · Pierre, SD

Mid-level

2026-04-09

SD 2026-04-09

View full posting on CareerOneStop → ID: e18a6a9b8988

Data Scientist (5190)

SMX · Santa Fe, NM

Mid-level

2026-04-09

NM 2026-04-09

View full posting on CareerOneStop → ID: cf145228080a

Data Scientist (5190)

SMX · Lincoln, NE

Mid-level

2026-04-09

NE 2026-04-09

View full posting on CareerOneStop → ID: 20117eb9fc5b

Data Scientist (5190)

SMX · Topeka, KS

Mid-level

2026-04-09

KS 2026-04-09

View full posting on CareerOneStop → ID: 932b148e006f

Data Scientist (5190)

SMX · Oklahoma City, OK

Mid-level

2026-04-09

OK 2026-04-09

View full posting on CareerOneStop → ID: a5e1b3817825

Data Scientist (5190)

SMX · Little Rock, AR

Mid-level

2026-04-09

AR 2026-04-09

View full posting on CareerOneStop → ID: 4ff3ef55c1c5

Data Scientist (5190)

SMX · Baton Rouge, LA

Mid-level

2026-04-09

LA 2026-04-09

View full posting on CareerOneStop → ID: 341157ef87bd

Data Scientist (5190)

SMX · Jackson, MS

Mid-level

2026-04-09

MS 2026-04-09

View full posting on CareerOneStop → ID: 1e9adb78fc9f

Data Scientist (5190)

SMX · Montgomery, AL

Mid-level

2026-04-09

AL 2026-04-09

View full posting on CareerOneStop → ID: ffb8c9b0b217

Data Scientist (Starlink)

SpaceX · Redmond, WA

Mid-level

2026-04-08

WA 2026-04-08

View full posting on CareerOneStop → ID: c1c722066c0b

Operations Research Analyst / Data Scientist (Remote)

GovCIO · Olympia, WA

Mid-level

2026-04-08

WA 2026-04-08

View full posting on CareerOneStop → ID: eb24ade14ae5

Operations Research Analyst / Data Scientist (Remote)

GovCIO · Boise, ID

Mid-level

2026-04-08

ID 2026-04-08

View full posting on CareerOneStop → ID: c4107b6525e4

Operations Research Analyst / Data Scientist (Remote)

GovCIO · Salem, OR

Mid-level

2026-04-08

OR 2026-04-08

View full posting on CareerOneStop → ID: 3dc638905f64

Operations Research Analyst / Data Scientist (Remote)

GovCIO · Helena, MT

Mid-level

2026-04-08

MT 2026-04-08

View full posting on CareerOneStop → ID: 2b439f6e6c88

Operations Research Analyst / Data Scientist (Remote)

GovCIO · Cheyenne, WY

Mid-level

2026-04-08

WY 2026-04-08

View full posting on CareerOneStop → ID: a8f4331edeeb

Operations Research Analyst / Data Scientist (Remote)

GovCIO · Carson City, NV

Mid-level

2026-04-08

NV 2026-04-08

View full posting on CareerOneStop → ID: 3f1d0dcd2018

Operations Research Analyst / Data Scientist (Remote)

GovCIO · Bismarck, ND

Mid-level

2026-04-08

ND 2026-04-08

View full posting on CareerOneStop → ID: 21504f2294d4

Operations Research Analyst / Data Scientist (Remote)

GovCIO · Pierre, SD

Mid-level

2026-04-08

SD 2026-04-08

View full posting on CareerOneStop → ID: 2dfd23e9b681

Operations Research Analyst / Data Scientist (Remote)

GovCIO · Santa Fe, NM

Mid-level

2026-04-08

NM 2026-04-08

View full posting on CareerOneStop → ID: 312f78d1f5d6

Operations Research Analyst / Data Scientist (Remote)

GovCIO · Lincoln, NE

Mid-level

2026-04-08

NE 2026-04-08

View full posting on CareerOneStop → ID: a6b8fcd7cdd7

Operations Research Analyst / Data Scientist (Remote)

GovCIO · Topeka, KS

Mid-level

2026-04-08

KS 2026-04-08

View full posting on CareerOneStop → ID: d5ac1387d33b

Operations Research Analyst / Data Scientist (Remote)

GovCIO · Oklahoma City, OK

Mid-level

2026-04-08

OK 2026-04-08

View full posting on CareerOneStop → ID: 4e3555ad57bb

Operations Research Analyst / Data Scientist (Remote)

GovCIO · Little Rock, AR

Mid-level

2026-04-08

AR 2026-04-08

View full posting on CareerOneStop → ID: e4f90219b6e8

Operations Research Analyst / Data Scientist (Remote)

GovCIO · Baton Rouge, LA

Mid-level

2026-04-08

LA 2026-04-08

View full posting on CareerOneStop → ID: 23b54332db29

Operations Research Analyst / Data Scientist (Remote)

GovCIO · Jackson, MS

Mid-level

2026-04-08

MS 2026-04-08

View full posting on CareerOneStop → ID: 9b1e91705467

Data Scientist II

Indeed · Portland, OR

Mid-level

2026-04-07

WA 2026-04-07

View full posting on CareerOneStop → ID: c0e919f02e1c

Data Scientist II

Indeed · Boise, ID

Mid-level

2026-04-07

ID 2026-04-07

View full posting on CareerOneStop → ID: d8b2b4e45cad

Data Scientist II

Indeed · Helena, MT

Mid-level

2026-04-07

MT 2026-04-07

View full posting on CareerOneStop → ID: 8104ba673ebc

Data Scientist II

Indeed · Cheyenne, WY

Mid-level

2026-04-07

WY 2026-04-07

View full posting on CareerOneStop → ID: 7dabd5f8fd84

Data Scientist II

Indeed · Las Vegas, NV

Mid-level

2026-04-07

NV 2026-04-07

View full posting on CareerOneStop → ID: e4a1ad55d3bf

Data Scientist II

Indeed · Bismarck, ND

Mid-level

2026-04-07

ND 2026-04-07

View full posting on CareerOneStop → ID: 97bc34c5a581

Data Scientist II

Indeed · Sioux Falls, SD

Mid-level

2026-04-07

SD 2026-04-07

View full posting on CareerOneStop → ID: de2a24ac78b7

Data Scientist II

Indeed · Albuquerque, NM

Mid-level

2026-04-07

NM 2026-04-07

View full posting on CareerOneStop → ID: a3fa3e1eea5a

Data Scientist II

Indeed · Omaha, NE

Mid-level

2026-04-07

NE 2026-04-07

View full posting on CareerOneStop → ID: f05e6438bd3a

Data Scientist II

Indeed · Kansas City, KS

Mid-level

2026-04-07

KS 2026-04-07

View full posting on CareerOneStop → ID: 8fa15f7a5940

Data Scientist II

Indeed · Oklahoma City, OK

Mid-level

2026-04-07

OK 2026-04-07

View full posting on CareerOneStop → ID: f9cb2291bac3

Data Scientist II

Indeed · Little Rock, AR

Mid-level

2026-04-07

AR 2026-04-07

View full posting on CareerOneStop → ID: 117d4b68c4c2

Data Scientist II

Indeed · Baton Rouge, LA

Mid-level

2026-04-07

LA 2026-04-07

View full posting on CareerOneStop → ID: 478f1ef8ad42

Data Scientist II

Indeed · Jackson, MS

Mid-level

2026-04-07

MS 2026-04-07

View full posting on CareerOneStop → ID: 62281102fe7b

Theoretical Biology and Biophysics Post-Bachelor Student in Data Science

Los Alamos National Laboratory · Los Alamos, NM

Mid-level

2026-04-04

NM 2026-04-04

View full posting on CareerOneStop → ID: fe44532a5af7

AI Agent ML Engineer

Bausch + Lomb · Boise, ID

Mid-level

2026-04-03

ID 2026-04-03

View full posting on CareerOneStop → ID: fd9fd3a4eb4e

AI Agent ML Engineer

Bausch + Lomb · Cheyenne, WY

Mid-level

2026-04-03

WY 2026-04-03

View full posting on CareerOneStop → ID: 39138df87c49

AI Agent ML Engineer

Bausch + Lomb · Lincoln, NE

Mid-level

2026-04-03

NE 2026-04-03

View full posting on CareerOneStop → ID: a5e11d1bd2e3

AI Agent ML Engineer

Bausch + Lomb · Topeka, KS

Mid-level

2026-04-03

KS 2026-04-03

View full posting on CareerOneStop → ID: e1b3589e6dbc

AI Agent ML Engineer

Bausch + Lomb · Oklahoma City, OK

Mid-level

2026-04-03

OK 2026-04-03

View full posting on CareerOneStop → ID: 1f53ee4cb3b7

AI Agent ML Engineer

Bausch + Lomb · Little Rock, AR

Mid-level

2026-04-03

AR 2026-04-03

View full posting on CareerOneStop → ID: 98b7888fb55b

AI Agent ML Engineer

Bausch + Lomb · Baton Rouge, LA

Mid-level

2026-04-03

LA 2026-04-03

View full posting on CareerOneStop → ID: b8525f1f67ce

AI Agent ML Engineer

Bausch + Lomb · Jackson, MS

Mid-level

2026-04-03

MS 2026-04-03

View full posting on CareerOneStop → ID: 238764fb1150

Actuarial and Data Science Model Validation

The Hartford · Olympia, WA

Mid-level

2026-04-01

WA 2026-04-01

View full posting on CareerOneStop → ID: 8278027d43dd

Actuarial and Data Science Model Validation

The Hartford · Boise, ID

Mid-level

2026-04-01

ID 2026-04-01

View full posting on CareerOneStop → ID: 62c8781ca8ec

Actuarial and Data Science Model Validation

The Hartford · Salem, OR

Mid-level

2026-04-01

OR 2026-04-01

View full posting on CareerOneStop → ID: f74ef62aaa4b

Actuarial and Data Science Model Validation

The Hartford · Helena, MT

Mid-level

2026-04-01

MT 2026-04-01

View full posting on CareerOneStop → ID: 28da9722469c

Actuarial and Data Science Model Validation

The Hartford · Cheyenne, WY

Mid-level

2026-04-01

WY 2026-04-01

View full posting on CareerOneStop → ID: 8e28441d7e2a

Actuarial and Data Science Model Validation

The Hartford · Carson City, NV

Mid-level

2026-04-01

NV 2026-04-01

View full posting on CareerOneStop → ID: 20c1e859e03c

Actuarial and Data Science Model Validation

The Hartford · Bismarck, ND

Mid-level

2026-04-01

ND 2026-04-01

View full posting on CareerOneStop → ID: b780a9c33bf5

Actuarial and Data Science Model Validation

The Hartford · Pierre, SD

Mid-level

2026-04-01

SD 2026-04-01

View full posting on CareerOneStop → ID: 1cf65c865591

Actuarial and Data Science Model Validation

The Hartford · Santa Fe, NM

Mid-level

2026-04-01

NM 2026-04-01

View full posting on CareerOneStop → ID: 5bce41bc8a89

Actuarial and Data Science Model Validation

The Hartford · Lincoln, NE

Mid-level

2026-04-01

NE 2026-04-01

View full posting on CareerOneStop → ID: 8e9f5bbef672

Actuarial and Data Science Model Validation

The Hartford · Oklahoma City, OK

Mid-level

2026-04-01

OK 2026-04-01

View full posting on CareerOneStop → ID: d2010924f6e7

Actuarial and Data Science Model Validation

The Hartford · Little Rock, AR

Mid-level

2026-04-01

AR 2026-04-01

View full posting on CareerOneStop → ID: 1718464afa1e

Actuarial and Data Science Model Validation

The Hartford · Baton Rouge, LA

Mid-level

2026-04-01

LA 2026-04-01

View full posting on CareerOneStop → ID: f4b0463cf9a5

Actuarial and Data Science Model Validation

The Hartford · Jackson, MS

Mid-level

2026-04-01

MS 2026-04-01

View full posting on CareerOneStop → ID: 7f3be2beaeaa

Data Scientist

BECU · Tukwila, WA

Mid-level

2026-03-27

WA 2026-03-27

View full posting on CareerOneStop → ID: 6dde6fb8be71

Data Scientist

T-Mobile USA, Inc · Bellevue, WA

Mid-level

2026-03-24

WA 2026-03-24

View full posting on CareerOneStop → ID: 66e30c7505de

Data Scientist III

Simplot · Boise, ID

Mid-level

2026-03-24

ID 2026-03-24

View full posting on CareerOneStop → ID: 109a952b4467

Data Scientist, Demand Forecasting

Amazon · Bellevue, WA

Mid-level

2026-03-18

WA 2026-03-18

View full posting on CareerOneStop → ID: 267794908dcf

Data Scientist

SOS International LLC · Salem, OR

Mid-level

2026-03-18

OR 2026-03-18

View full posting on CareerOneStop → ID: fc33e9cfa2dc

(USA) Data Scientist III

Walmart · Bentonville, AR

Mid-level

2026-03-17

AR 2026-03-17

View full posting on CareerOneStop → ID: 0c04047ed4c5

Data Scientist, Amazon Leo Global Planning, Amazon Leo

Amazon · Bellevue, WA

Mid-level

2026-03-14

WA 2026-03-14

View full posting on CareerOneStop → ID: 9cbbceb50354

Machine Learning Scientist - GenAI, KIT

Amazon · Bellevue, WA

Mid-level

2026-03-13

WA 2026-03-13

View full posting on CareerOneStop → ID: d0513bb1c063

Data Scientist, Amazon Leo Global Planning, Amazon Leo

Amazon · Bellevue, WA

Mid-level

2026-03-13

WA 2026-03-13

View full posting on CareerOneStop → ID: ac40f88c9ae9

Data Scientist

The Gores Group, LLC · Remote, OR

Mid-level

2026-03-08

OR 2026-03-08

View full posting on CareerOneStop → ID: 85ee686aef51

Machine Learning Engineer

Micron Technology, Inc. · Boise, ID

Mid-level

2026-03-07

ID 2026-03-07

View full posting on CareerOneStop → ID: a6a0c7355d59

Data Scientist

Micron Technology, Inc. · Boise, ID

Mid-level

2026-03-06

ID 2026-03-06

View full posting on CareerOneStop → ID: 522af9f32aff

Data Scientist 4

Bucher & Christian Consulting, Inc. dba BCforward (BCF) · Redmond, WA

Mid-level

2026-03-05

WA 2026-03-05

View full posting on CareerOneStop → ID: cbd4751c7b60

Data Scientist, Rapid & Rural Logistics (R2L)

Amazon · Bellevue, WA

Mid-level

2026-02-27

WA 2026-02-27

View full posting on CareerOneStop → ID: a358c0d3070d

Data Scientist

Capgemini · Bellevue, WA

Mid-level

2026-02-14

WA 2026-02-14

View full posting on CareerOneStop → ID: 58e118dde5e8

Post-Baccalaureate Student in Computer Science and Data Science for Materials Characterization

Los Alamos National Laboratory · Los Alamos, NM

Mid-level

2026-02-04

NM 2026-02-04

View full posting on CareerOneStop → ID: 98e421945659

Data Scientist, LM Simulations Engineering, AMZL Simulations & Analytics Engineering

Amazon · Bellevue, WA

Mid-level

2026-02-01

WA 2026-02-01

View full posting on CareerOneStop → ID: 5f389c4f72f9

AI Agent ML Engineer

Bausch + Lomb · Olympia, WA

Mid-level

2026-01-27

WA 2026-01-27

View full posting on CareerOneStop → ID: a90f86807435

AI Agent ML Engineer

Bausch + Lomb · Salem, OR

Mid-level

2026-01-27

OR 2026-01-27

View full posting on CareerOneStop → ID: 0c4cfad75528

AI Agent ML Engineer

Bausch + Lomb · Helena, MT

Mid-level

2026-01-27

MT 2026-01-27

View full posting on CareerOneStop → ID: 7f9042d9da4e

AI Agent ML Engineer

Bausch + Lomb · Bismarck, ND

Mid-level

2026-01-27

ND 2026-01-27

View full posting on CareerOneStop → ID: ea6f4617a652

AI Agent ML Engineer

Bausch + Lomb · Pierre, SD

Mid-level

2026-01-27

SD 2026-01-27

View full posting on CareerOneStop → ID: 0f562f50fe4c

AI Agent ML Engineer

Bausch + Lomb · Santa Fe, NM

Mid-level

2026-01-27

NM 2026-01-27

View full posting on CareerOneStop → ID: 74e15064f028

Data Scientist

Insight Global · Portland, OR

Mid-level

2026-01-23

WA 2026-01-23

View full posting on CareerOneStop → ID: 55331c8f9841

Data Scientist

Leidos · Omaha, NE

Mid-level

2026-01-10

NE 2026-01-10

View full posting on CareerOneStop → ID: 49511e1bd1ae

Data Scientist II

Microsoft Corporation · Redmond, WA

Mid-level

2025-12-21

WA 2025-12-21

View full posting on CareerOneStop → ID: 5b4e6e51a63b

Machine Learning Scientist II

Microsoft Corporation · Redmond, WA

Mid-level

2025-12-20

WA 2025-12-20

View full posting on CareerOneStop → ID: 4b1f65d85ecc

Human Performance Data Scientist II

General Dynamics Information Technology · Mcchord Afb, WA

Mid-level

2025-12-04

WA 2025-12-04

View full posting on CareerOneStop → ID: 1bf5c4ea4c34

Data Scientist, SCOT Forecasting and Labs - CIV Team

Amazon · Bellevue, WA

Mid-level

2025-07-22

WA 2025-07-22

View full posting on CareerOneStop → ID: b4266522b631

Software Engineer, Machine Learning

Meta · Olympia, WA

Mid-level

2025-07-19

WA 2025-07-19

View full posting on CareerOneStop → ID: 9bf84b2b91c9

Software Engineer, Machine Learning

Meta · Olympia, WA

Mid-level

2025-07-19

WA 2025-07-19

View full posting on CareerOneStop → ID: 5e4b5b2806e1

Software Engineer, Machine Learning

Meta · Boise, ID

Mid-level

2025-07-19

ID 2025-07-19

View full posting on CareerOneStop → ID: ba87e9a8a6e6

Software Engineer, Machine Learning

Meta · Salem, OR

Mid-level

2025-07-19

OR 2025-07-19

View full posting on CareerOneStop → ID: 2dab5875a07e

Software Engineer, Machine Learning

Meta · Salem, OR

Mid-level

2025-07-19

OR 2025-07-19

View full posting on CareerOneStop → ID: 00c5be86b94a

Software Engineer, Machine Learning

Meta · Helena, MT

Mid-level

2025-07-19

MT 2025-07-19

View full posting on CareerOneStop → ID: 3b7ae35a6290

Software Engineer, Machine Learning

Meta · Cheyenne, WY

Mid-level

2025-07-19

WY 2025-07-19

View full posting on CareerOneStop → ID: fdc343f8d69d

Software Engineer, Machine Learning

Meta · Cheyenne, WY

Mid-level

2025-07-19

WY 2025-07-19

View full posting on CareerOneStop → ID: 762d43c9695e

Software Engineer, Machine Learning

Meta · Bismarck, ND

Mid-level

2025-07-19

ND 2025-07-19

View full posting on CareerOneStop → ID: 97356abc7b2c

Software Engineer, Machine Learning

Meta · Bismarck, ND

Mid-level

2025-07-19

ND 2025-07-19

View full posting on CareerOneStop → ID: a7827d6268b7

Software Engineer, Machine Learning

Meta · Pierre, SD

Mid-level

2025-07-19

SD 2025-07-19

View full posting on CareerOneStop → ID: b5db950c2ba6

Software Engineer, Machine Learning

Meta · Pierre, SD

Mid-level

2025-07-19

SD 2025-07-19

View full posting on CareerOneStop → ID: b2b784bcbf74

Software Engineer, Machine Learning

Meta · Redmond, WA

Mid-level

2025-07-09

WA 2025-07-09

View full posting on CareerOneStop → ID: 1712d7e86420

Software Engineer, Machine Learning

Meta · Redmond, WA

Mid-level

2025-07-09

WA 2025-07-09

View full posting on CareerOneStop → ID: ac83f545533e

Software Engineer, Machine Learning

Meta · Olympia, WA

Mid-level

2025-06-27

WA 2025-06-27

View full posting on CareerOneStop → ID: 88d4c79b19ef

Software Engineer, Machine Learning

Meta · Olympia, WA

Mid-level

2025-06-27

WA 2025-06-27

View full posting on CareerOneStop → ID: df4bbca20659

Software Engineer, Machine Learning

Meta · Bellevue, WA

Mid-level

2025-06-27

WA 2025-06-27

View full posting on CareerOneStop → ID: 4d0a38f4cabd

Software Engineer, Machine Learning

Meta · Bellevue, WA

Mid-level

2025-06-27

WA 2025-06-27

View full posting on CareerOneStop → ID: 90e22cd1e9b1

Software Engineer, Machine Learning

Meta · Boise, ID

Mid-level

2025-06-27

ID 2025-06-27

View full posting on CareerOneStop → ID: a3e6db61716f

Software Engineer, Machine Learning

Meta · Salem, OR

Mid-level

2025-06-27

OR 2025-06-27

View full posting on CareerOneStop → ID: 96bf34a0a307

Software Engineer, Machine Learning

Meta · Salem, OR

Mid-level

2025-06-27

OR 2025-06-27

View full posting on CareerOneStop → ID: ef877e3813b7

Software Engineer, Machine Learning

Meta · Helena, MT

Mid-level

2025-06-27

MT 2025-06-27

View full posting on CareerOneStop → ID: 41621a2eb0a4

Software Engineer, Machine Learning

Meta · Cheyenne, WY

Mid-level

2025-06-27

WY 2025-06-27

View full posting on CareerOneStop → ID: 4de8da760254

Software Engineer, Machine Learning

Meta · Cheyenne, WY

Mid-level

2025-06-27

WY 2025-06-27

View full posting on CareerOneStop → ID: 7fd745ee67f4

Software Engineer, Machine Learning

Meta · Bismarck, ND

Mid-level

2025-06-27

ND 2025-06-27

View full posting on CareerOneStop → ID: 866ca3a68b6f

Software Engineer, Machine Learning

Meta · Bismarck, ND

Mid-level

2025-06-27

ND 2025-06-27

View full posting on CareerOneStop → ID: ed9698c2c87d

Software Engineer, Machine Learning

Meta · Pierre, SD

Mid-level

2025-06-27

SD 2025-06-27

View full posting on CareerOneStop → ID: af2569a752c7

Software Engineer, Machine Learning

Meta · Pierre, SD

Mid-level

2025-06-27

SD 2025-06-27

View full posting on CareerOneStop → ID: 4fb34366646d

Software Engineer, Machine Learning

Meta · Bellevue, WA

Mid-level

2025-06-25

WA 2025-06-25

View full posting on CareerOneStop → ID: 3d4de48a9c8f

Data Scientist, Product Analytics

Meta · Olympia, WA

Mid-level

2024-12-05

WA 2024-12-05

View full posting on CareerOneStop → ID: 1b3eb089ac01

Data Scientist, Product Analytics

Meta · Olympia, WA

Mid-level

2024-12-05

WA 2024-12-05

View full posting on CareerOneStop → ID: 48f35c309984

Data Scientist, Product Analytics

Meta · Boise, ID

Mid-level

2024-12-05

ID 2024-12-05

View full posting on CareerOneStop → ID: 21df90ba7356

Data Scientist, Product Analytics

Meta · Salem, OR

Mid-level

2024-12-05

OR 2024-12-05

View full posting on CareerOneStop → ID: 80ab85d714a5

Data Scientist, Product Analytics

Meta · Salem, OR

Mid-level

2024-12-05

OR 2024-12-05

View full posting on CareerOneStop → ID: 67366d4ff18f

Data Scientist, Product Analytics

Meta · Helena, MT

Mid-level

2024-12-05

MT 2024-12-05

View full posting on CareerOneStop → ID: 841eae6a75f8

Data Scientist, Product Analytics

Meta · Cheyenne, WY

Mid-level

2024-12-05

WY 2024-12-05

View full posting on CareerOneStop → ID: c188436dfe3f

Data Scientist, Product Analytics

Meta · Cheyenne, WY

Mid-level

2024-12-05

WY 2024-12-05

View full posting on CareerOneStop → ID: 86daa8f395e0

Data Scientist, Product Analytics

Meta · Bismarck, ND

Mid-level

2024-12-05

ND 2024-12-05

View full posting on CareerOneStop → ID: 439ef77721a4

Data Scientist, Product Analytics

Meta · Bismarck, ND

Mid-level

2024-12-05

ND 2024-12-05

View full posting on CareerOneStop → ID: 0f7058cbebcd

Data Scientist, Product Analytics

Meta · Pierre, SD

Mid-level

2024-12-05

SD 2024-12-05

View full posting on CareerOneStop → ID: d16b0f64fe8a

Data Scientist, Product Analytics

Meta · Pierre, SD

Mid-level

2024-12-05

SD 2024-12-05

View full posting on CareerOneStop → ID: 7aa1c62c2041

Data Scientist, Product Analytics

Meta · Olympia, WA

Mid-level

2024-12-03

WA 2024-12-03

View full posting on CareerOneStop → ID: 30c1aa8db12f

Data Scientist, Product Analytics

Meta · Olympia, WA

Mid-level

2024-12-03

WA 2024-12-03

View full posting on CareerOneStop → ID: d848fcc46918

Data Scientist, Product Analytics

Meta · Boise, ID

Mid-level

2024-12-03

ID 2024-12-03

View full posting on CareerOneStop → ID: e45df11201a1

Data Scientist, Product Analytics

Meta · Salem, OR

Mid-level

2024-12-03

OR 2024-12-03

View full posting on CareerOneStop → ID: f547fdb3d4c9

Data Scientist, Product Analytics

Meta · Salem, OR

Mid-level

2024-12-03

OR 2024-12-03

View full posting on CareerOneStop → ID: e46dc8757e1d

Data Scientist, Product Analytics

Meta · Bellevue, WA

Mid-level

2024-10-24

WA 2024-10-24

View full posting on CareerOneStop → ID: dd45c760ed40