Job Matches
Washington job postings for occupations your coursework prepares you for. Sorted by how many of the occupation's tasks your courses cover.
Demo profile: Math BS with Data Science minor. Sign in (GitHub) to rank these jobs against your own courses, projects, internships, and work experience — each added signal sharpens the qualification match.
50 Washington postings
across 1 occupation the EWU Math BS prepares you for
· ranked by how many tasks your 16 declared courses cover.
Showing CareerOneStop postings from the last 30 days; the scraper re-syncs from CareerOneStop nightly. Last posting in this list dated 2026-06-05.
Scraper last re-confirmed a WA posting 2026-06-05 11:59 (434 touched today).
Showing CareerOneStop postings from the last 30 days; the scraper re-syncs from CareerOneStop nightly. Last posting in this list dated 2026-06-05.
Scraper last re-confirmed a WA posting 2026-06-05 11:59 (434 touched today).
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15/16
tasks
Senior Data Scientist IV - Gen AI Development & Evaluation
Pacific Northwest National Laboratory
Richland, WA
2026-06-05
Tasks you're prepared for
(15 of 16 for Data Scientists)
- Analyze, manipulate, or process large sets of data using statistical software.
-
Apply feature selection algorithms to models predicting outcomes of interest, such as sales, attrition, and healthcare use.
via CSCD 484
- Apply sampling techniques to determine groups to be surveyed or use complete enumeration methods.
- Clean and manipulate raw data using statistical software.
- Compare models using statistical performance metrics, such as loss functions or proportion of explained variance.
+10 more covered tasks
Tasks you'd need to develop
(1)
Recommend data-driven solutions to key stakeholders.
These could be filled by an applied project, elective, or internship — see the program page for examples.
15/16
tasks
Senior Data Scientist IV - AI Safety
Pacific Northwest National Laboratory
Richland, WA
2026-06-05
Tasks you're prepared for
(15 of 16 for Data Scientists)
- Analyze, manipulate, or process large sets of data using statistical software.
-
Apply feature selection algorithms to models predicting outcomes of interest, such as sales, attrition, and healthcare use.
via CSCD 484
- Apply sampling techniques to determine groups to be surveyed or use complete enumeration methods.
- Clean and manipulate raw data using statistical software.
- Compare models using statistical performance metrics, such as loss functions or proportion of explained variance.
+10 more covered tasks
Tasks you'd need to develop
(1)
Recommend data-driven solutions to key stakeholders.
These could be filled by an applied project, elective, or internship — see the program page for examples.
15/16
tasks
Machine Learning Research Engineer , Text Generation, Input Experience
Apple
Seattle, WA
2026-06-05
Role Number: 200666539-3337 Summary 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 ou
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)
What you'd do
- 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 ea… 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… 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 optimizat… 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 ski… 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.
Nice to have
- 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
Tasks you're prepared for
(15 of 16 for Data Scientists)
- Analyze, manipulate, or process large sets of data using statistical software.
-
Apply feature selection algorithms to models predicting outcomes of interest, such as sales, attrition, and healthcare use.
via CSCD 484
- Apply sampling techniques to determine groups to be surveyed or use complete enumeration methods.
- Clean and manipulate raw data using statistical software.
- Compare models using statistical performance metrics, such as loss functions or proportion of explained variance.
+10 more covered tasks
Tasks you'd need to develop
(1)
Recommend data-driven solutions to key stakeholders.
These could be filled by an applied project, elective, or internship — see the program page for examples.
15/16
tasks
Machine Learning Engineer - Visual Intelligence
Apple
Seattle, WA
2026-06-05
Weekly Hours: 40 Role Number: 200666805-3337 Summary 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 le
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 int… 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
What you'd do
- 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 … 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 back… 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.
Nice to have
- 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
Tasks you're prepared for
(15 of 16 for Data Scientists)
- Analyze, manipulate, or process large sets of data using statistical software.
-
Apply feature selection algorithms to models predicting outcomes of interest, such as sales, attrition, and healthcare use.
via CSCD 484
- Apply sampling techniques to determine groups to be surveyed or use complete enumeration methods.
- Clean and manipulate raw data using statistical software.
- Compare models using statistical performance metrics, such as loss functions or proportion of explained variance.
+10 more covered tasks
Tasks you'd need to develop
(1)
Recommend data-driven solutions to key stakeholders.
These could be filled by an applied project, elective, or internship — see the program page for examples.
15/16
tasks
EY-Parthenon - Strategy and Execution - Growth Platforms - Data Scientist - Sr Associate/Consultant
EY
Seattle, WA
2026-06-05
Location: Atlanta, Boston, Chicago, Dallas, Denver, Detroit, Houston, Los Angeles, McLean, New York, Hoboken, Philadelphia, San Francisco, Seattle At EY, we're all in to shape your future with confidence. We'll help you succeed in a globally connected powerhouse of diverse teams and take your ca
Requirements
- Outstanding academic performance, with a bachelor's degree and at least 2 years of related work experience; or a graduate degree and approximately 18 months of related work experience.?
- Experience in data engineering or hybrid data science roles focused on pipeline scalability and schema management.
- Familiarity in cloud-native data infrastructure (e.g., GCP/AWS, Snowflake, BigQuery, Databricks, Delta Lake).
- Strong SQL/Python/Scala proficiency and experience with orchestration tools (Airflow, dbt).
What you'd do
- The EY Growth Platforms Data Scientist Senior Associate/Consultant will play a critical role building and scaling our multi-source data pipelines- sourcing, merging, and transforming data assets that … The EY Growth Platforms Data Scientist Senior Associate/Consultant will play a critical role building and scaling our multi-source data pipelines- sourcing, merging, and transforming data assets that power high-visibility client engagements. This role will participate in building, cleaning, transforming, and enriching data to power AI/ML-driven agents and dashboards, and collaborate with Business leaders and C-level executives to get hands-on experience solving some of the most interesting and mission-critical business questions with data.
- *Skills and attributes for success
- Lead ingestion and ETL design for structured and semi-structured data (CSV, JSON, APIs, Flat Files).
- Understand schema, data quality, and transformation logic for multiple sources on a client-by-client like NAIC, NOAA, Google Trends, EBRI, Cannex, LIMRA, and internal client logs.
Tasks you're prepared for
(15 of 16 for Data Scientists)
- Analyze, manipulate, or process large sets of data using statistical software.
-
Apply feature selection algorithms to models predicting outcomes of interest, such as sales, attrition, and healthcare use.
via CSCD 484
- Apply sampling techniques to determine groups to be surveyed or use complete enumeration methods.
- Clean and manipulate raw data using statistical software.
- Compare models using statistical performance metrics, such as loss functions or proportion of explained variance.
+10 more covered tasks
Tasks you'd need to develop
(1)
Recommend data-driven solutions to key stakeholders.
These could be filled by an applied project, elective, or internship — see the program page for examples.
15/16
tasks
EY-Parthenon - Strategy and Execution - Growth Platforms - AI/ML Engineer - Sr Associate/Consultant
EY
Seattle, WA
2026-06-05
Location: Atlanta, Boston, Chicago, Dallas, Denver, Detroit, Houston, Los Angeles, McLean, New York, Hoboken, Philadelphia, San Francisco, Seattle At EY, we're all in to shape your future with confidence. We'll help you succeed in a globally connected powerhouse of diverse teams and take your ca
Requirements
- Outstanding academic performance, with a bachelor's degree and at least 2 years of related work experience; or a graduate degree and approximately 18 months of related work experience.?
- Familiarity with multi-modal agent frameworks (LangChain, Haystack, RAG pipelines).
- Knowledge in vector databases (e.g., Pinecone, Weaviate, Chroma), retrieval systems, and LLM fine-tuning.
- Strong understanding of real-world structured data merging, schema linking, and model evaluation at scale.
What you'd do
- The EY Growth Platforms AI ML Engineering Senior Associate/Consultant will play a critical role building and maintaining our core advanced analytics platform and serving the technical execution lead f… The EY Growth Platforms AI ML Engineering Senior Associate/Consultant will play a critical role building and maintaining our core advanced analytics platform and serving the technical execution lead for high-visibility client engagements. You'll work with Business leaders and C-level executives to translate business needs into technically executable ML agentic workflows and work alongside a high-performing team of engineers and contractors through end-to-end project lifecycles.
- *Skills and attributes for success
- Partner with Business and Strategy Leads to translate business needs into executable AI workflows, data pipelines, and client-specific product specifications.
- Assist in defining the end-to-end architecture for agents that integrate LLMs, retrieval-augmented generation (RAG), multi-source data ingestion, and analytics components.
Tasks you're prepared for
(15 of 16 for Data Scientists)
- Analyze, manipulate, or process large sets of data using statistical software.
-
Apply feature selection algorithms to models predicting outcomes of interest, such as sales, attrition, and healthcare use.
via CSCD 484
- Apply sampling techniques to determine groups to be surveyed or use complete enumeration methods.
- Clean and manipulate raw data using statistical software.
- Compare models using statistical performance metrics, such as loss functions or proportion of explained variance.
+10 more covered tasks
Tasks you'd need to develop
(1)
Recommend data-driven solutions to key stakeholders.
These could be filled by an applied project, elective, or internship — see the program page for examples.
15/16
tasks
Distinguished, Data Scientist
Walmart
Bellevue, WA
2026-06-05
Position Summary... What you'll do... As a Distinguished Data Scientist in the Marketplace data sciences team, you'll have the opportunity to - + Drive innovative strategic solutionsfor Marketplaceutilizingadvanced SOTA AI and ML solutions at large scale and atacceleratedpace. + Dri
Requirements
- Bachelor's with >20years, Masters > 17yearsOR Ph.D. in Comp Science/Statistics/Mathematics with > 14years of relevant experience. Educational qualifications should be Computer Science/Statistics/Mathe… Bachelor's with >20years, Masters > 17yearsOR Ph.D. in Comp Science/Statistics/Mathematics with > 14years of relevant experience. Educational qualifications should be Computer Science/Statistics/Mathematics ora related area.
- Experience of acting as a tech lead for > 10 years
- _Outlined below are the required minimum qualifications for this position. If none are listed, there are no minimum qualifications._
- Option 1: Bachelor's degree in Statistics, Economics, Analytics, Mathematics, Computer Science, Information Technology or related field and 6 years' experience in an analytics related field. Option 2:… Option 1: Bachelor's degree in Statistics, Economics, Analytics, Mathematics, Computer Science, Information Technology or related field and 6 years' experience in an analytics related field. Option 2: Master's degree in Statistics, Economics, Analytics, Mathematics, Computer Science, Information Technology or related field and 4 years' experience in an analytics related field. Option 3: 8 years' experience in an analytics or related field.
What you'd do
- As a Distinguished Data Scientist in the Marketplace data sciences team, you'll have the opportunity to -
- Drive innovative strategic solutionsfor Marketplaceutilizingadvanced SOTA AI and ML solutions at large scale and atacceleratedpace.
- Drive data-derived insights by developing advanced statistical models, machine learning algorithms and computational algorithms based on business initiatives
- Work closely with Directors, Sr. Managers of Data Science, and leaders ofArchitecture,Engineering,Product& businessteams to drive the Organizational strategy aroundMarketplace.
Nice to have
- _Outlined below are the optional preferred qualifications for this position. If none are listed, there are no preferred qualifications._
- Data science, machine learning, optimization models, PhD in Machine Learning, Computer Science, Information Technology, Operations Research, Statistics, Applied Mathematics, Econometrics, Publications… Data science, machine learning, optimization models, PhD in Machine Learning, Computer Science, Information Technology, Operations Research, Statistics, Applied Mathematics, Econometrics, Publications or active peer reviewer in related journals or conference, Successful completion of one or more assessments in Python, Spark, Scala, or R, Using open source frameworks (for example, scikit learn, tensorflow, torch), We value candidates with a background in creating inclusive digital experiences, demonstrating knowledge in implementing Web Content Accessibility Guidelines (WCAG) 2.2 AA standards, assistive technologies, and integrating digital accessibility seamlessly. The ideal candidate would have knowledge of accessibility best practices and join us as we continue to create accessible products and services following Walmart's accessibility standards and guidelines for supporting an inclusive culture.
- *Primary Location...
- 10900 Ne 4th St, Bellevue, WA 98004, United States of America
Tasks you're prepared for
(15 of 16 for Data Scientists)
- Analyze, manipulate, or process large sets of data using statistical software.
-
Apply feature selection algorithms to models predicting outcomes of interest, such as sales, attrition, and healthcare use.
via CSCD 484
- Apply sampling techniques to determine groups to be surveyed or use complete enumeration methods.
- Clean and manipulate raw data using statistical software.
- Compare models using statistical performance metrics, such as loss functions or proportion of explained variance.
+10 more covered tasks
Tasks you'd need to develop
(1)
Recommend data-driven solutions to key stakeholders.
These could be filled by an applied project, elective, or internship — see the program page for examples.
15/16
tasks
Data Scientist, Fleet Planning , Global Fleet Products
Amazon
Bellevue, WA
2026-06-05
Description Amazon Global Fleet and Products (GFP) organization is responsible for fleet programs and capacity. The Fleet Planning team is looking for a Data Scientist to drive the most efficient use of fleet. Amazon Middle and Last Mile fleet planning is a complex resource allocation problem. T
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 scie… 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
What you'd do
- 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.
Nice to have
- 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
Tasks you're prepared for
(15 of 16 for Data Scientists)
- Analyze, manipulate, or process large sets of data using statistical software.
-
Apply feature selection algorithms to models predicting outcomes of interest, such as sales, attrition, and healthcare use.
via CSCD 484
- Apply sampling techniques to determine groups to be surveyed or use complete enumeration methods.
- Clean and manipulate raw data using statistical software.
- Compare models using statistical performance metrics, such as loss functions or proportion of explained variance.
+10 more covered tasks
Tasks you'd need to develop
(1)
Recommend data-driven solutions to key stakeholders.
These could be filled by an applied project, elective, or internship — see the program page for examples.
15/16
tasks
Data Scientist, Finance
Meta
Bellevue, WA
2026-06-05
Summary: 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
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)
What you'd do
- 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 … 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
Nice to have
- 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
Tasks you're prepared for
(15 of 16 for Data Scientists)
- Analyze, manipulate, or process large sets of data using statistical software.
-
Apply feature selection algorithms to models predicting outcomes of interest, such as sales, attrition, and healthcare use.
via CSCD 484
- Apply sampling techniques to determine groups to be surveyed or use complete enumeration methods.
- Clean and manipulate raw data using statistical software.
- Compare models using statistical performance metrics, such as loss functions or proportion of explained variance.
+10 more covered tasks
Tasks you'd need to develop
(1)
Recommend data-driven solutions to key stakeholders.
These could be filled by an applied project, elective, or internship — see the program page for examples.
15/16
tasks
Data Scientist Engineer - SFL Scientific
Deloitte
Seattle, WA
2026-06-05
Our Deloitte Strategy & Transactions team helps guide clients through their most critical moments and transformational initiatives. From strategy to execution, this team delivers integrated, end-to-end support and advisory services covering valuation modeling, cost optimization, restructuring, busin
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 i… 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
Nice to have
- 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
Tasks you're prepared for
(15 of 16 for Data Scientists)
- Analyze, manipulate, or process large sets of data using statistical software.
-
Apply feature selection algorithms to models predicting outcomes of interest, such as sales, attrition, and healthcare use.
via CSCD 484
- Apply sampling techniques to determine groups to be surveyed or use complete enumeration methods.
- Clean and manipulate raw data using statistical software.
- Compare models using statistical performance metrics, such as loss functions or proportion of explained variance.
+10 more covered tasks
Tasks you'd need to develop
(1)
Recommend data-driven solutions to key stakeholders.
These could be filled by an applied project, elective, or internship — see the program page for examples.
15/16
tasks
AI and Data Science Engineer III
Deloitte
Seattle, WA
2026-06-05
AI Data Science Engineer III Our Deloitte Human Capital team transforms technology platforms, drives innovation, and helps make a significant impact on our clients' success. We are hiring a Senior Consultant in Data Science to join our Human Capital practice and help shape the future of workforce
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.
What you'd do
- 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.
Nice to have
- 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.
Tasks you're prepared for
(15 of 16 for Data Scientists)
- Analyze, manipulate, or process large sets of data using statistical software.
-
Apply feature selection algorithms to models predicting outcomes of interest, such as sales, attrition, and healthcare use.
via CSCD 484
- Apply sampling techniques to determine groups to be surveyed or use complete enumeration methods.
- Clean and manipulate raw data using statistical software.
- Compare models using statistical performance metrics, such as loss functions or proportion of explained variance.
+10 more covered tasks
Tasks you'd need to develop
(1)
Recommend data-driven solutions to key stakeholders.
These could be filled by an applied project, elective, or internship — see the program page for examples.
15/16
tasks
(USA) Senior, Data Scientist
Walmart
Bellevue, WA
2026-06-05
Position Summary... What you'll do... *Immigration Sponsorship support will NOT be available for this position* Join Marketplace Tech to help power a fast-growing, two-sided platform connecting customers with third-party sellers at massive scale. As a Data Scientist, you'll turn c
Requirements
- Very good knowledge of the foundations of machine learning and statistics
- Experience in Analyzing the Complex Problems and translate it into data science algorithms
- Experience in machine learning, supervised and unsupervised and deep learning.
- Hands on experience in Computer Visions and NLP. Gen AI, Agentic AI
What you'd do
- *Immigration Sponsorship support will NOT be available for this position Join Marketplace Tech to help power a fast-growing, two-sided platform connecting customers with third-party sellers at massive… *Immigration Sponsorship support will NOT be available for this position Join Marketplace Tech to help power a fast-growing, two-sided platform connecting customers with third-party sellers at massive scale. As a Data Scientist, you'll turn complex marketplace data into actionable insights and production-ready models that improve seller success, customer experience, trust & safety, and overall marketplace growth. You'll partner closely with product, engineering, and business teams to define success metrics, run experiments, build predictive and causal solutions, and communicate clear recommendations that drive measurable impact. Immigration Sponsorship support will NOT be available for this
- Drive data-derived insights across the wide range of retail divisions by developing advanced statistical models, machine learning algorithms and computational algorithms based on business initiatives
- Direct the gathering of data, assessing data validity and synthesizing data into large analytics datasets to support project goals
- Utilize big data analytics and advanced data science techniques to identify trends, patterns, and discrepancies in data. Determine additional data needed to support insights
Nice to have
- _Outlined below are the optional preferred qualifications for this position. If none are listed, there are no preferred qualifications._
- Data science, machine learning, optimization models, Master's degree in Machine Learning, Computer Science, Information Technology, Operations Research, Statistics, Applied Mathematics, Econometrics, … Data science, machine learning, optimization models, Master's degree in Machine Learning, Computer Science, Information Technology, Operations Research, Statistics, Applied Mathematics, Econometrics, Successful completion of one or more assessments in Python, Spark, Scala, or R, Using open source frameworks (for example, scikit learn, tensorflow, torch), We value candidates with a background in creating inclusive digital experiences, demonstrating knowledge in implementing Web Content Accessibility Guidelines (WCAG) 2.2 AA standards, assistive technologies, and integrating digital accessibility seamlessly. The ideal candidate would have knowledge of accessibility best practices and join us as we continue to create accessible products and services following Walmart's accessibility standards and guidelines for supporting an inclusive culture.
- *Primary Location...
- 10900 Ne 4th St, Bellevue, WA 98004, United States of America
Tasks you're prepared for
(15 of 16 for Data Scientists)
- Analyze, manipulate, or process large sets of data using statistical software.
-
Apply feature selection algorithms to models predicting outcomes of interest, such as sales, attrition, and healthcare use.
via CSCD 484
- Apply sampling techniques to determine groups to be surveyed or use complete enumeration methods.
- Clean and manipulate raw data using statistical software.
- Compare models using statistical performance metrics, such as loss functions or proportion of explained variance.
+10 more covered tasks
Tasks you'd need to develop
(1)
Recommend data-driven solutions to key stakeholders.
These could be filled by an applied project, elective, or internship — see the program page for examples.
15/16
tasks
Data Scientist Engineer - SFL Scientific
Deloitte
Portland, OR
2026-06-05
Tasks you're prepared for
(15 of 16 for Data Scientists)
- Analyze, manipulate, or process large sets of data using statistical software.
-
Apply feature selection algorithms to models predicting outcomes of interest, such as sales, attrition, and healthcare use.
via CSCD 484
- Apply sampling techniques to determine groups to be surveyed or use complete enumeration methods.
- Clean and manipulate raw data using statistical software.
- Compare models using statistical performance metrics, such as loss functions or proportion of explained variance.
+10 more covered tasks
Tasks you'd need to develop
(1)
Recommend data-driven solutions to key stakeholders.
These could be filled by an applied project, elective, or internship — see the program page for examples.
15/16
tasks
AI and Data Science Engineer III
Deloitte
Portland, OR
2026-06-05
Tasks you're prepared for
(15 of 16 for Data Scientists)
- Analyze, manipulate, or process large sets of data using statistical software.
-
Apply feature selection algorithms to models predicting outcomes of interest, such as sales, attrition, and healthcare use.
via CSCD 484
- Apply sampling techniques to determine groups to be surveyed or use complete enumeration methods.
- Clean and manipulate raw data using statistical software.
- Compare models using statistical performance metrics, such as loss functions or proportion of explained variance.
+10 more covered tasks
Tasks you'd need to develop
(1)
Recommend data-driven solutions to key stakeholders.
These could be filled by an applied project, elective, or internship — see the program page for examples.
15/16
tasks
Staff, Data Scientist
Walmart
Bellevue, WA
2026-06-05
Tasks you're prepared for
(15 of 16 for Data Scientists)
- Analyze, manipulate, or process large sets of data using statistical software.
-
Apply feature selection algorithms to models predicting outcomes of interest, such as sales, attrition, and healthcare use.
via CSCD 484
- Apply sampling techniques to determine groups to be surveyed or use complete enumeration methods.
- Clean and manipulate raw data using statistical software.
- Compare models using statistical performance metrics, such as loss functions or proportion of explained variance.
+10 more covered tasks
Tasks you'd need to develop
(1)
Recommend data-driven solutions to key stakeholders.
These could be filled by an applied project, elective, or internship — see the program page for examples.
15/16
tasks
Sr. Data Scientist, WW Insurance & Claim
Amazon
Bellevue, WA
2026-06-05
Tasks you're prepared for
(15 of 16 for Data Scientists)
- Analyze, manipulate, or process large sets of data using statistical software.
-
Apply feature selection algorithms to models predicting outcomes of interest, such as sales, attrition, and healthcare use.
via CSCD 484
- Apply sampling techniques to determine groups to be surveyed or use complete enumeration methods.
- Clean and manipulate raw data using statistical software.
- Compare models using statistical performance metrics, such as loss functions or proportion of explained variance.
+10 more covered tasks
Tasks you'd need to develop
(1)
Recommend data-driven solutions to key stakeholders.
These could be filled by an applied project, elective, or internship — see the program page for examples.
15/16
tasks
Principal, Data Scientist
Walmart
Bellevue, WA
2026-06-05
Tasks you're prepared for
(15 of 16 for Data Scientists)
- Analyze, manipulate, or process large sets of data using statistical software.
-
Apply feature selection algorithms to models predicting outcomes of interest, such as sales, attrition, and healthcare use.
via CSCD 484
- Apply sampling techniques to determine groups to be surveyed or use complete enumeration methods.
- Clean and manipulate raw data using statistical software.
- Compare models using statistical performance metrics, such as loss functions or proportion of explained variance.
+10 more covered tasks
Tasks you'd need to develop
(1)
Recommend data-driven solutions to key stakeholders.
These could be filled by an applied project, elective, or internship — see the program page for examples.
15/16
tasks
Software Engineer in Natural Language Processing (NLP) and Machine Learning (ML)
Apple
Seattle, WA
2026-06-05
Tasks you're prepared for
(15 of 16 for Data Scientists)
- Analyze, manipulate, or process large sets of data using statistical software.
-
Apply feature selection algorithms to models predicting outcomes of interest, such as sales, attrition, and healthcare use.
via CSCD 484
- Apply sampling techniques to determine groups to be surveyed or use complete enumeration methods.
- Clean and manipulate raw data using statistical software.
- Compare models using statistical performance metrics, such as loss functions or proportion of explained variance.
+10 more covered tasks
Tasks you'd need to develop
(1)
Recommend data-driven solutions to key stakeholders.
These could be filled by an applied project, elective, or internship — see the program page for examples.
15/16
tasks
Senior Data Scientist IV - Gen AI Development & Evaluation
Pacific Northwest National Laboratory
Seattle, WA
2026-06-05
Tasks you're prepared for
(15 of 16 for Data Scientists)
- Analyze, manipulate, or process large sets of data using statistical software.
-
Apply feature selection algorithms to models predicting outcomes of interest, such as sales, attrition, and healthcare use.
via CSCD 484
- Apply sampling techniques to determine groups to be surveyed or use complete enumeration methods.
- Clean and manipulate raw data using statistical software.
- Compare models using statistical performance metrics, such as loss functions or proportion of explained variance.
+10 more covered tasks
Tasks you'd need to develop
(1)
Recommend data-driven solutions to key stakeholders.
These could be filled by an applied project, elective, or internship — see the program page for examples.
15/16
tasks
Senior Data Scientist IV - AI Safety
Pacific Northwest National Laboratory
Seattle, WA
2026-06-05
Tasks you're prepared for
(15 of 16 for Data Scientists)
- Analyze, manipulate, or process large sets of data using statistical software.
-
Apply feature selection algorithms to models predicting outcomes of interest, such as sales, attrition, and healthcare use.
via CSCD 484
- Apply sampling techniques to determine groups to be surveyed or use complete enumeration methods.
- Clean and manipulate raw data using statistical software.
- Compare models using statistical performance metrics, such as loss functions or proportion of explained variance.
+10 more covered tasks
Tasks you'd need to develop
(1)
Recommend data-driven solutions to key stakeholders.
These could be filled by an applied project, elective, or internship — see the program page for examples.
15/16
tasks
Data Scientist - Pricing
Microsoft Corporation
Redmond, WA
2026-06-04
Overview The Cloud and AI Platforms Monetization organization is a big picture team that encourages a diverse and inclusive culture. We are growth strategists who enable the Microsoft mission by creating durable profit growth through high-impact monetization strategies, packaging, and pricing.
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 str… 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 str… 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.
What you'd do
- 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 impa… 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.
Nice to have
- 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 a… 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 struc… 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 str… 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
Tasks you're prepared for
(15 of 16 for Data Scientists)
- Analyze, manipulate, or process large sets of data using statistical software.
-
Apply feature selection algorithms to models predicting outcomes of interest, such as sales, attrition, and healthcare use.
via CSCD 484
- Apply sampling techniques to determine groups to be surveyed or use complete enumeration methods.
- Clean and manipulate raw data using statistical software.
- Compare models using statistical performance metrics, such as loss functions or proportion of explained variance.
+10 more covered tasks
Tasks you'd need to develop
(1)
Recommend data-driven solutions to key stakeholders.
These could be filled by an applied project, elective, or internship — see the program page for examples.
15/16
tasks
Machine Learning Engineer
Robinhood Markets, Inc.
Bellevue, WA
2026-06-04
Tasks you're prepared for
(15 of 16 for Data Scientists)
- Analyze, manipulate, or process large sets of data using statistical software.
-
Apply feature selection algorithms to models predicting outcomes of interest, such as sales, attrition, and healthcare use.
via CSCD 484
- Apply sampling techniques to determine groups to be surveyed or use complete enumeration methods.
- Clean and manipulate raw data using statistical software.
- Compare models using statistical performance metrics, such as loss functions or proportion of explained variance.
+10 more covered tasks
Tasks you'd need to develop
(1)
Recommend data-driven solutions to key stakeholders.
These could be filled by an applied project, elective, or internship — see the program page for examples.
15/16
tasks
Data Scientist I, Demand Forecasting
Amazon
Bellevue, WA
2026-06-04
Description Amazon has the world's most complex supply chain: we fulfill global demand for hundreds of millions of products at lightning fast delivery speeds. We need your skills to optimize our supply chain, with the end goal of delighting our customers. A core part of the supply chain operations
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/research scientist, statistician or quantitative analyst in an internet-based company with complex and big data sources experience
- Bachelor's degree
- Familiarity with large language models (LLMs) or generative AI applications in analytics or explainability
What you'd do
- Design and analyze experiments (A/B tests) to measure the impact of forecast model changes and SCOT initiatives, drawing causal inferences from both experimental and observational data
- Develop bias correction models to improve forecast accuracy across Amazon's demand forecasting systems, including National, Regional, Grocery, SSD, Inbound, and CIV forecasts
- Contribute to GenAI/LLM-based research for forecast explainability and interpretability, helping stakeholders understand what drives forecast signals
- Support and enhance the Labs experimentation platform by building scalable inference and measurement solutions that quantify the impact of forecasting improvements
Nice to have
- 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)
- Experience with time series forecasting, demand modeling, or bias correction techniques
Tasks you're prepared for
(15 of 16 for Data Scientists)
- Analyze, manipulate, or process large sets of data using statistical software.
-
Apply feature selection algorithms to models predicting outcomes of interest, such as sales, attrition, and healthcare use.
via CSCD 484
- Apply sampling techniques to determine groups to be surveyed or use complete enumeration methods.
- Clean and manipulate raw data using statistical software.
- Compare models using statistical performance metrics, such as loss functions or proportion of explained variance.
+10 more covered tasks
Tasks you'd need to develop
(1)
Recommend data-driven solutions to key stakeholders.
These could be filled by an applied project, elective, or internship — see the program page for examples.
15/16
tasks
(USA) Staff, Data Scientist
Walmart
Bellevue, WA
2026-06-04
Tasks you're prepared for
(15 of 16 for Data Scientists)
- Analyze, manipulate, or process large sets of data using statistical software.
-
Apply feature selection algorithms to models predicting outcomes of interest, such as sales, attrition, and healthcare use.
via CSCD 484
- Apply sampling techniques to determine groups to be surveyed or use complete enumeration methods.
- Clean and manipulate raw data using statistical software.
- Compare models using statistical performance metrics, such as loss functions or proportion of explained variance.
+10 more covered tasks
Tasks you'd need to develop
(1)
Recommend data-driven solutions to key stakeholders.
These could be filled by an applied project, elective, or internship — see the program page for examples.
15/16
tasks
(USA) Staff, Data Scientist
Walmart
Bellevue, WA
2026-06-04
Tasks you're prepared for
(15 of 16 for Data Scientists)
- Analyze, manipulate, or process large sets of data using statistical software.
-
Apply feature selection algorithms to models predicting outcomes of interest, such as sales, attrition, and healthcare use.
via CSCD 484
- Apply sampling techniques to determine groups to be surveyed or use complete enumeration methods.
- Clean and manipulate raw data using statistical software.
- Compare models using statistical performance metrics, such as loss functions or proportion of explained variance.
+10 more covered tasks
Tasks you'd need to develop
(1)
Recommend data-driven solutions to key stakeholders.
These could be filled by an applied project, elective, or internship — see the program page for examples.
15/16
tasks
(USA) Senior Distinguished I, Data Scientist
Walmart
Bellevue, WA
2026-06-04
Tasks you're prepared for
(15 of 16 for Data Scientists)
- Analyze, manipulate, or process large sets of data using statistical software.
-
Apply feature selection algorithms to models predicting outcomes of interest, such as sales, attrition, and healthcare use.
via CSCD 484
- Apply sampling techniques to determine groups to be surveyed or use complete enumeration methods.
- Clean and manipulate raw data using statistical software.
- Compare models using statistical performance metrics, such as loss functions or proportion of explained variance.
+10 more covered tasks
Tasks you'd need to develop
(1)
Recommend data-driven solutions to key stakeholders.
These could be filled by an applied project, elective, or internship — see the program page for examples.
15/16
tasks
Staff AI/ML Engineer - Future Sensing, Embodied AI
General Motors
Olympia, WA
2026-06-04
Job Description At General Motors, our product teams are redefining mobility. Through a human-centered design process, we create vehicles and experiences that are designed not just to be seen, but to be felt. We're turning today's impossible into tomorrow's standard -from breakthrough hardware
What you'd do
- At General Motors, our product teams are redefining mobility. Through a human-centered design process, we create vehicles and experiences that are designed not just to be seen, but to be felt. We're t… At General Motors, our product teams are redefining mobility. Through a human-centered design process, we create vehicles and experiences that are designed not just to be seen, but to be felt. We're turning today's impossible into tomorrow's standard -from breakthrough hardware and battery systems to intuitive design, intelligent software, and next-generation safety and entertainment features. Every day, our products move millions of people as we aim to make driving safer, smarter, and more connected, shaping the future of transportation on a global scale. Are you passionate about accelerating the future of autonomous driving? Join the Embodied AI team at General Motors. Our team is developing and deploying machine learning solutions that support safe and reliable autonomous vehicle behavior across real-world scenarios.
- As a Staff AI/ML Future Sensing Engineer in the Embodied AI organization, you will serve as a senior individual contributor driving end-to-end technical work that informs next-generation sensing archi… As a Staff AI/ML Future Sensing Engineer in the Embodied AI organization, you will serve as a senior individual contributor driving end-to-end technical work that informs next-generation sensing architecture decisions. You will help define and evaluate machine learning and perception solutions that directly impact autonomous driving performance, with emphasis on future sensing architectures, multi-modal sensor fusion, system integration, and the technical evidence required to support sensor and compute decisions.
- In this role, you will partner closely with cross-functional engineering teams, contribute to core technical direction within your domain, and support the growth of engineers through technical collabo… In this role, you will partner closely with cross-functional engineering teams, contribute to core technical direction within your domain, and support the growth of engineers through technical collaboration and mentorship. You will help translate research into scalable onboard ML and perception solutions while contributing to the continuous improvement of GM's autonomy stack and sensing strategy.
- *What You'll Do
Nice to have
- Experience in robotics or autonomous driving systems
- Experience with architecting perception or sensory systems for automotive, robotics, or safety-critical platforms
- Experience with system integration across sensors, calibration, compute, and onboard software pipelines
- Experience with simulation, synthetic data, and sim-to-road evaluation workflows
Tasks you're prepared for
(15 of 16 for Data Scientists)
- Analyze, manipulate, or process large sets of data using statistical software.
-
Apply feature selection algorithms to models predicting outcomes of interest, such as sales, attrition, and healthcare use.
via CSCD 484
- Apply sampling techniques to determine groups to be surveyed or use complete enumeration methods.
- Clean and manipulate raw data using statistical software.
- Compare models using statistical performance metrics, such as loss functions or proportion of explained variance.
+10 more covered tasks
Tasks you'd need to develop
(1)
Recommend data-driven solutions to key stakeholders.
These could be filled by an applied project, elective, or internship — see the program page for examples.
15/16
tasks
Senior AI/ML Engineer - Future Sensing, Embodied AI
General Motors
Olympia, WA
2026-06-04
Job Description At General Motors, our product teams are redefining mobility. Through a human-centered design process, we create vehicles and experiences that are designed not just to be seen, but to be felt. We're turning today's impossible into tomorrow's standard -from breakthrough hardware
What you'd do
- At General Motors, our product teams are redefining mobility. Through a human-centered design process, we create vehicles and experiences that are designed not just to be seen, but to be felt. We're t… At General Motors, our product teams are redefining mobility. Through a human-centered design process, we create vehicles and experiences that are designed not just to be seen, but to be felt. We're turning today's impossible into tomorrow's standard -from breakthrough hardware and battery systems to intuitive design, intelligent software, and next-generation safety and entertainment features. Every day, our products move millions of people as we aim to make driving safer, smarter, and more connected, shaping the future of transportation on a global scale. Are you passionate about accelerating the future of autonomous driving? Join the Embodied AI team at General Motors. Our team is developing and deploying machine learning solutions that support safe and reliable autonomous vehicle behavior across real-world scenarios.
- As a Senior AI/ML Future Sensing Engineer in the Embodied AI organization, you will develop and evaluate machine learning solutions contributing to future sensing architecture decisions and autonomous… As a Senior AI/ML Future Sensing Engineer in the Embodied AI organization, you will develop and evaluate machine learning solutions contributing to future sensing architecture decisions and autonomous driving performance. You will contribute to designing and improving ML and perception models that support safe and reliable vehicle behavior across real-world scenarios, while helping connect sensing choices to measurable performance outcomes.
- You will collaborate closely with senior engineers and cross-functional teams to translate research and technical concepts into production-ready or production-informing solutions while contributing to… You will collaborate closely with senior engineers and cross-functional teams to translate research and technical concepts into production-ready or production-informing solutions while contributing to engineering best practices, technical analyses, and delivery execution.
- *What You'll Do
Nice to have
- Experience withperceptionsensors including cameras, radar, and lida
- Experience with multi-modal sensor fusion and system integration
- Experience with production ML pipelines, model optimization, and performance tuning
- Experience with simulation, synthetic data, or scenario-based evaluation
Tasks you're prepared for
(15 of 16 for Data Scientists)
- Analyze, manipulate, or process large sets of data using statistical software.
-
Apply feature selection algorithms to models predicting outcomes of interest, such as sales, attrition, and healthcare use.
via CSCD 484
- Apply sampling techniques to determine groups to be surveyed or use complete enumeration methods.
- Clean and manipulate raw data using statistical software.
- Compare models using statistical performance metrics, such as loss functions or proportion of explained variance.
+10 more covered tasks
Tasks you'd need to develop
(1)
Recommend data-driven solutions to key stakeholders.
These could be filled by an applied project, elective, or internship — see the program page for examples.
15/16
tasks
Staff Machine Learning Engineer - News, Books, and Stocks Team
Apple
Seattle, WA
2026-06-04
Role Number: 200647772-3337 Summary 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
Requirements
- MS in Machine Learning, Computer Science, or related field. Alternatively, equivalent industry experience to an MS degree is acceptable.
- At least 5 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.
- Experience designing user-facing machine learning features with interdisciplinary partners.
What you'd do
- 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
Nice to have
- Experience in a technical leadership role.
Tasks you're prepared for
(15 of 16 for Data Scientists)
- Analyze, manipulate, or process large sets of data using statistical software.
-
Apply feature selection algorithms to models predicting outcomes of interest, such as sales, attrition, and healthcare use.
via CSCD 484
- Apply sampling techniques to determine groups to be surveyed or use complete enumeration methods.
- Clean and manipulate raw data using statistical software.
- Compare models using statistical performance metrics, such as loss functions or proportion of explained variance.
+10 more covered tasks
Tasks you'd need to develop
(1)
Recommend data-driven solutions to key stakeholders.
These could be filled by an applied project, elective, or internship — see the program page for examples.
15/16
tasks
Senior Machine Learning Engineering Manager, Ad Platforms
The Walt Disney Company
Seattle, WA
2026-06-04
Technology is at the heart of Disney's past, present, and future. Disney Entertainment and ESPN Product & Technology is a global organization of engineers, product developers, designers, technologists, data scientists, and more - all working to build and advance the technological backbone for Disney
Requirements
- Bachelor's or master's degree in computer science, Engineering, Mathematics, Statistics, or a related field.
- 10+ years of relevant industry experience, with at least 5 years in people-management managing senior ICs and managers.
- Proven ability to translate business problems into scalable ML and GenAI solutions and strong understanding of machine learning fundamentals, deep learning, and statistical modeling.
- Proven experience designing, building, and deploying scalable machine learning models and systems in production.
What you'd do
- You will apply your battle-tested experience, deep technical knowledge of software and systems including Machine Learning and AI technologies, and leadership skills to unblock and guide our ML/AI team… You will apply your battle-tested experience, deep technical knowledge of software and systems including Machine Learning and AI technologies, and leadership skills to unblock and guide our ML/AI team members to design and build scalable, performant, maintainable, and testable models and pipelines in various domains using industry best practices which are aligned in close collaboration with the ML team in the US highlighting cross-functional collaboration.
- Daily, you should bring:
- A willingness and desire to effectively communicate and collaborate across teams and systems on architecture, design, and implementation.
- A passion for mentoring, learning, and taking on new challenges.
Nice to have
- Domain knowledge in the Ad Tech industry
- Experience working with large-scale data and distributed systems.
- Knowledge of cloud platforms (e.g., AWS, GCP, Azure) and MLOps pipelines.
- Track record of innovation and contributions to the ML/AI community (publications, talks, open source).
Tasks you're prepared for
(15 of 16 for Data Scientists)
- Analyze, manipulate, or process large sets of data using statistical software.
-
Apply feature selection algorithms to models predicting outcomes of interest, such as sales, attrition, and healthcare use.
via CSCD 484
- Apply sampling techniques to determine groups to be surveyed or use complete enumeration methods.
- Clean and manipulate raw data using statistical software.
- Compare models using statistical performance metrics, such as loss functions or proportion of explained variance.
+10 more covered tasks
Tasks you'd need to develop
(1)
Recommend data-driven solutions to key stakeholders.
These could be filled by an applied project, elective, or internship — see the program page for examples.
15/16
tasks
Manager, Machine Learning Engineering - Ad Platforms
The Walt Disney Company
Seattle, WA
2026-06-04
Technology is at the heart of Disney's past, present, and future. Disney Entertainment and ESPN Product & Technology is a global organization of engineers, product developers, designers, technologists, data scientists, and more - all working to build and advance the technological backbone for Disney
Requirements
- Bachelor's or master's degree in computer science, Engineering,
- Mathematics, Statistics, or a related field.
- 8+ years of relevant industry experience, with at least 2-3 years in a people-management or technical leadership role.
- Proven ability to translate business problems into scalable ML and GenAI solutions and strong understanding of machine learning fundamentals, deep learning, and statistical modeling.
What you'd do
- You will apply your battle-tested experience, deep technical knowledge of software and systems including Machine Learning and AI technologies, and leadership skills to unblock and guide our ML/AI team… You will apply your battle-tested experience, deep technical knowledge of software and systems including Machine Learning and AI technologies, and leadership skills to unblock and guide our ML/AI team members to design and build scalable, performant, maintainable, and testable models and pipelines in various domains using industry best practices which are aligned in close collaboration with the ML team in the US highlighting cross-functional collaboration.
- Daily, you should bring:
- A willingness and desire to effectively communicate and collaborate across teams and systems on architecture, design, and implementation.
- A passion for mentoring, learning, and taking on new challenges.
Nice to have
- Domain knowledge in the Ad Tech industry
- Experience working with large-scale data and distributed systems.
- Knowledge of cloud platforms (e.g., AWS, GCP, Azure) and MLOps pipelines.
- Track record of innovation and contributions to the ML/AI community (publications, talks, open source).
Tasks you're prepared for
(15 of 16 for Data Scientists)
- Analyze, manipulate, or process large sets of data using statistical software.
-
Apply feature selection algorithms to models predicting outcomes of interest, such as sales, attrition, and healthcare use.
via CSCD 484
- Apply sampling techniques to determine groups to be surveyed or use complete enumeration methods.
- Clean and manipulate raw data using statistical software.
- Compare models using statistical performance metrics, such as loss functions or proportion of explained variance.
+10 more covered tasks
Tasks you'd need to develop
(1)
Recommend data-driven solutions to key stakeholders.
These could be filled by an applied project, elective, or internship — see the program page for examples.
15/16
tasks
Machine Learning Engineer - News, Books, and Stocks Team
Apple
Seattle, WA
2026-06-04
Role Number: 200660323-3337 Summary 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 cons
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.
What you'd do
- 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 ma… 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 co… 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!
Nice to have
- 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.)
Tasks you're prepared for
(15 of 16 for Data Scientists)
- Analyze, manipulate, or process large sets of data using statistical software.
-
Apply feature selection algorithms to models predicting outcomes of interest, such as sales, attrition, and healthcare use.
via CSCD 484
- Apply sampling techniques to determine groups to be surveyed or use complete enumeration methods.
- Clean and manipulate raw data using statistical software.
- Compare models using statistical performance metrics, such as loss functions or proportion of explained variance.
+10 more covered tasks
Tasks you'd need to develop
(1)
Recommend data-driven solutions to key stakeholders.
These could be filled by an applied project, elective, or internship — see the program page for examples.
15/16
tasks
Data Scientist, Technology Consulting, AI & Data, Government & Public Sector (Manager)(Multiple Posi
EY Government Services LLC
Seattle, WA
2026-06-04
Tasks you're prepared for
(15 of 16 for Data Scientists)
- Analyze, manipulate, or process large sets of data using statistical software.
-
Apply feature selection algorithms to models predicting outcomes of interest, such as sales, attrition, and healthcare use.
via CSCD 484
- Apply sampling techniques to determine groups to be surveyed or use complete enumeration methods.
- Clean and manipulate raw data using statistical software.
- Compare models using statistical performance metrics, such as loss functions or proportion of explained variance.
+10 more covered tasks
Tasks you'd need to develop
(1)
Recommend data-driven solutions to key stakeholders.
These could be filled by an applied project, elective, or internship — see the program page for examples.
15/16
tasks
AIML - ML Engineer, Responsible AI
Apple
Seattle, WA
2026-06-04
Weekly Hours: 40 Role Number: 200642026-3337 Summary 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,
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
What you'd do
- 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 futu… 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 … 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
Nice to have
- 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
Tasks you're prepared for
(15 of 16 for Data Scientists)
- Analyze, manipulate, or process large sets of data using statistical software.
-
Apply feature selection algorithms to models predicting outcomes of interest, such as sales, attrition, and healthcare use.
via CSCD 484
- Apply sampling techniques to determine groups to be surveyed or use complete enumeration methods.
- Clean and manipulate raw data using statistical software.
- Compare models using statistical performance metrics, such as loss functions or proportion of explained variance.
+10 more covered tasks
Tasks you'd need to develop
(1)
Recommend data-driven solutions to key stakeholders.
These could be filled by an applied project, elective, or internship — see the program page for examples.
15/16
tasks
AI and Data Science Engineer II
Deloitte
Seattle, WA
2026-06-04
Our Deloitte Customer team empowers organizations to build deeper relationships with customers through innovative strategies, advanced analytics, Generative AI, transformative technologies, and creative design. We can enhance customer experiences and drive sustained growth and customer value creatio
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
Nice to have
- 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
Tasks you're prepared for
(15 of 16 for Data Scientists)
- Analyze, manipulate, or process large sets of data using statistical software.
-
Apply feature selection algorithms to models predicting outcomes of interest, such as sales, attrition, and healthcare use.
via CSCD 484
- Apply sampling techniques to determine groups to be surveyed or use complete enumeration methods.
- Clean and manipulate raw data using statistical software.
- Compare models using statistical performance metrics, such as loss functions or proportion of explained variance.
+10 more covered tasks
Tasks you'd need to develop
(1)
Recommend data-driven solutions to key stakeholders.
These could be filled by an applied project, elective, or internship — see the program page for examples.
15/16
tasks
Senior Staff Research Data Scientist, DevIE
Google
Kirkland, WA
2026-06-03
Senior Staff Research Data Scientist, DevIE _corporate_fare_ Google _place_ Sunnyvale, CA, USA; Kirkland, WA, USA; +2 more; +1 more Advanced Experience owning outcomes and decision making, solving ambiguous problems and influencing stakeholders; deep expertise in domain. _info_outline_
Requirements
- Master's degree in Statistics, Data Science, Mathematics, Physics, Economics, Operations Research, Engineering, or a related quantitative field.
- 10 years of work experience using analytics to solve product or business problems, coding (e.g., Python, R, SQL), querying databases or statistical analysis, or 8 years of work experience with a PhD degree.
What you'd do
- Our mission is to accelerate Google's velocity by empowering developers with AI-ready knowledge, trusted content, and scaled and targeted enablement programs.
- We are looking for a Data Scientist (DS) who can work in a rapidly evolving tech landscape with novel methodologies, to generate actionable insights for product teams and leaders.
- In this role, you will engage deeply with Google DeepMind and the core of Google's AI capabilities. You will shape the investigative directions and strategies for Gemini, revealing actionable insights… In this role, you will engage deeply with Google DeepMind and the core of Google's AI capabilities. You will shape the investigative directions and strategies for Gemini, revealing actionable insights into how it integrates with Google's complex software engineering ecosystem. Additionally, you will drive an understanding of how various agentic capabilities affect software and model development workflows, leveraging these insights to optimize complex systems at a Google scale.
- The US base salary range for this full-time position is $262,000-$365,000 + bonus + equity + benefits. Our salary ranges are determined by role, level, and location. Within the range, individual pay i… The US base salary range for this full-time position is $262,000-$365,000 + 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.
Nice to have
- 12 years of work experience using analytics to solve product or business problems, coding (e.g., Python, R, SQL), querying databases or statistical analysis, or 10 years of work experience with a PhD degree.
Tasks you're prepared for
(15 of 16 for Data Scientists)
- Analyze, manipulate, or process large sets of data using statistical software.
-
Apply feature selection algorithms to models predicting outcomes of interest, such as sales, attrition, and healthcare use.
via CSCD 484
- Apply sampling techniques to determine groups to be surveyed or use complete enumeration methods.
- Clean and manipulate raw data using statistical software.
- Compare models using statistical performance metrics, such as loss functions or proportion of explained variance.
+10 more covered tasks
Tasks you'd need to develop
(1)
Recommend data-driven solutions to key stakeholders.
These could be filled by an applied project, elective, or internship — see the program page for examples.
15/16
tasks
Principal Machine Learning Engineer
Oracle
Olympia, WA
2026-06-03
Job Description At Oracle Cloud Infrastructure (OCI), we build the future of the cloud for Enterprises as a diverse team of fellow creators and inventors. We act with the speed and attitude of a start-up, with the scale and customer-focus of the leading enterprise software company in the world
Requirements
- BS/MS in Computer Science or equivalent experience
- 6-10+ years building and shipping enterprise distributed or cloud-native systems
- Experience scaling heterogeneous CPU/GPU training infrastructure for large multimodal frontier models
- Strong foundation in system design, distributed systems, and cloud architecture best practices
What you'd do
- At Oracle Cloud Infrastructure (OCI), we build the future of the cloud for Enterprises as a diverse team of fellow creators and inventors. We act with the speed and attitude of a start-up, with the sc… At Oracle Cloud Infrastructure (OCI), we build the future of the cloud for Enterprises as a diverse team of fellow creators and inventors. We act with the speed and attitude of a start-up, with the scale and customer-focus of the leading enterprise software company in the world.
- Values are OCI's foundation and how we deliver excellence. We strive for equity, inclusion, and respect for all. We are committed to the greater good in our products and our actions. We are constantly… Values are OCI's foundation and how we deliver excellence. We strive for equity, inclusion, and respect for all. We are committed to the greater good in our products and our actions. We are constantly learning and taking opportunities to grow our careers and ourselves. We challenge each other to stretch beyond our past to build our future.
- You are the builder here. You will be part of a team of smart, motivated, and diverse people and given the autonomy and support to do your best work. It is a dynamic and flexible workplace where you'l… You are the builder here. You will be part of a team of smart, motivated, and diverse people and given the autonomy and support to do your best work. It is a dynamic and flexible workplace where you'll belong and be encouraged.
- In? OCI ? AI Infrastructure ?org we are addressing exciting challenges at the intersection of artificial intelligence and cutting-edge cloud infrastructure. In this role, you will drive building state… In? OCI ? AI Infrastructure ?org we are addressing exciting challenges at the intersection of artificial intelligence and cutting-edge cloud infrastructure. In this role, you will drive building state-of-the-art training infrastructure for massive GPU clusters, as well as designing agentic systems deployed on OCI infrastructure at enterprise-scale. You will be innovating on leading principles of agentic software development and driving the frontier on infrastructure that maximizes the potential of bleeding-edge GPU clusters.
Nice to have
- Production experience with Cloud and ML technologies
- Experience working in the below areas and algorithms will be ideal but not mandatory:?
- Generative AI Modeling: Customizing LLM's, build and deploy LLM's at scale for large scale data generation
- Algorithms: Transformer models, Attention mechanism, Prompt tooling
Tasks you're prepared for
(15 of 16 for Data Scientists)
- Analyze, manipulate, or process large sets of data using statistical software.
-
Apply feature selection algorithms to models predicting outcomes of interest, such as sales, attrition, and healthcare use.
via CSCD 484
- Apply sampling techniques to determine groups to be surveyed or use complete enumeration methods.
- Clean and manipulate raw data using statistical software.
- Compare models using statistical performance metrics, such as loss functions or proportion of explained variance.
+10 more covered tasks
Tasks you'd need to develop
(1)
Recommend data-driven solutions to key stakeholders.
These could be filled by an applied project, elective, or internship — see the program page for examples.
15/16
tasks
Senior Machine Learning Engineer
Indeed
Portland, OR
2026-06-03
Our Mission As the world's number 1 job site*, our mission is to help people get jobs. We strive to cultivate an inclusive and accessible workplace where all people feel comfortable being themselves. We're looking to grow our teams with more people who share our enthusiasm for innovation and c
What you'd do
- As a Senior Machine Learning Engineer on our Sourcing team, you will work on developing and deploying ML and AI solutions in production. You'll be collaborating with a cross-functional product team to… As a Senior Machine Learning Engineer on our Sourcing team, you will work on developing and deploying ML and AI solutions in production. You'll be collaborating with a cross-functional product team to drive value and better customer experiences for our Sourcing product, which connects employers with new talent through AI. This Senior MLE will help us improve our automated outreach quality, building new agentic experiences, and LLMOps reliability and infrastructure.
- Autonomously deliver ML and AI projects, including prompt development and evaluation, training ML models, building LLM-as-a-Judge capabilities, and building recommendation / ranking systems
- Develop LLM and machine learning model improvements, scale them in production, and run iterative A/B tests to improve our Sourcing product
- Estimate potential business impact of AI and ML and balance tradeoffs between delivery velocity and systematic infrastructure investments
Tasks you're prepared for
(15 of 16 for Data Scientists)
- Analyze, manipulate, or process large sets of data using statistical software.
-
Apply feature selection algorithms to models predicting outcomes of interest, such as sales, attrition, and healthcare use.
via CSCD 484
- Apply sampling techniques to determine groups to be surveyed or use complete enumeration methods.
- Clean and manipulate raw data using statistical software.
- Compare models using statistical performance metrics, such as loss functions or proportion of explained variance.
+10 more covered tasks
Tasks you'd need to develop
(1)
Recommend data-driven solutions to key stakeholders.
These could be filled by an applied project, elective, or internship — see the program page for examples.
15/16
tasks
Machine Learning Engineering Manager
Indeed
Portland, OR
2026-06-03
Our Mission As the world's number 1 job site*, our mission is to help people get jobs. We strive to cultivate an inclusive and accessible workplace where all people feel comfortable being themselves. We're looking to grow our teams with more people who share our enthusiasm for innovation and c
What you'd do
- At Indeed, we are committed to delivering exceptional experiences that connect job seekers with opportunities through innovative technology. We integrate machine learning at every step to create consi… At Indeed, we are committed to delivering exceptional experiences that connect job seekers with opportunities through innovative technology. We integrate machine learning at every step to create consistent, engaging, and secure experiences that meet the needs of our users. Our teams consist of Software Engineers, UX Designers, Product Managers, and Machine Learning professionals collaborating across regions to drive impactful business outcomes.
- As a Machine Learning Engineering Manager, you will onboard and oversee junior scientists and technical leads, partnering closely with Product, Software Engineering, and UX teams. Your focus will incl… As a Machine Learning Engineering Manager, you will onboard and oversee junior scientists and technical leads, partnering closely with Product, Software Engineering, and UX teams. Your focus will include developing and innovating machine learning ecosystems that upgrade job seeker journey experience end to end
- Coach Machine Learning Engineers and Data Scientists on the Journey team to improve their performance, advise them on their career direction, and develop their qualifications.
- Work to understand, prioritize, and plan the team's work items without external guidance.
Tasks you're prepared for
(15 of 16 for Data Scientists)
- Analyze, manipulate, or process large sets of data using statistical software.
-
Apply feature selection algorithms to models predicting outcomes of interest, such as sales, attrition, and healthcare use.
via CSCD 484
- Apply sampling techniques to determine groups to be surveyed or use complete enumeration methods.
- Clean and manipulate raw data using statistical software.
- Compare models using statistical performance metrics, such as loss functions or proportion of explained variance.
+10 more covered tasks
Tasks you'd need to develop
(1)
Recommend data-driven solutions to key stakeholders.
These could be filled by an applied project, elective, or internship — see the program page for examples.
15/16
tasks
Associate Director, Data Science
Chewy Inc.
Bellevue, WA
2026-06-03
Associate Director, Data Science (Chewy, Inc.; Bellevue, Washington): Combine deep understanding of machine learning, advanced data analysis, statistical testing, and the ability to communicate insights effectively to both technical and non-technical stakeholders. Operate as a full stack data sc
Requirements
- Apply advanced mathematics and data science methodologies;
- Standard machine learning and statistical techniques including predictive models (time series, regression, etc.), classification, forecasting; and
Tasks you're prepared for
(15 of 16 for Data Scientists)
- Analyze, manipulate, or process large sets of data using statistical software.
-
Apply feature selection algorithms to models predicting outcomes of interest, such as sales, attrition, and healthcare use.
via CSCD 484
- Apply sampling techniques to determine groups to be surveyed or use complete enumeration methods.
- Clean and manipulate raw data using statistical software.
- Compare models using statistical performance metrics, such as loss functions or proportion of explained variance.
+10 more covered tasks
Tasks you'd need to develop
(1)
Recommend data-driven solutions to key stakeholders.
These could be filled by an applied project, elective, or internship — see the program page for examples.
15/16
tasks
Staff Machine Learning Engineer, AI Research
Cribl, Inc
Olympia, WA
2026-06-03
B2B SAAS data observability software. Join the company that's building the telemetry infrastructure for the AI era. At Cribl, we partner with IT and Security teams at many of the world's biggest enterprises, including half of the Fortune 100, to bridge the gap between AI ambition and infrastructur
Tasks you're prepared for
(15 of 16 for Data Scientists)
- Analyze, manipulate, or process large sets of data using statistical software.
-
Apply feature selection algorithms to models predicting outcomes of interest, such as sales, attrition, and healthcare use.
via CSCD 484
- Apply sampling techniques to determine groups to be surveyed or use complete enumeration methods.
- Clean and manipulate raw data using statistical software.
- Compare models using statistical performance metrics, such as loss functions or proportion of explained variance.
+10 more covered tasks
Tasks you'd need to develop
(1)
Recommend data-driven solutions to key stakeholders.
These could be filled by an applied project, elective, or internship — see the program page for examples.
15/16
tasks
Machine Learning Engineering Manager
Indeed
Seattle, WA
2026-06-03
Our Mission As the world's number 1 job site*, our mission is to help people get jobs. We strive to cultivate an inclusive and accessible workplace where all people feel comfortable being themselves. We're looking to grow our teams with more people who share our enthusiasm for innovation and c
What you'd do
- At Indeed, we are committed to delivering exceptional experiences that connect job seekers with opportunities through innovative technology. We integrate machine learning at every step to create consi… At Indeed, we are committed to delivering exceptional experiences that connect job seekers with opportunities through innovative technology. We integrate machine learning at every step to create consistent, engaging, and secure experiences that meet the needs of our users. Our teams consist of Software Engineers, UX Designers, Product Managers, and Machine Learning professionals collaborating across regions to drive impactful business outcomes.
- As a Machine Learning Engineering Manager, you will onboard and oversee junior scientists and technical leads, partnering closely with Product, Software Engineering, and UX teams. Your focus will incl… As a Machine Learning Engineering Manager, you will onboard and oversee junior scientists and technical leads, partnering closely with Product, Software Engineering, and UX teams. Your focus will include developing and innovating machine learning ecosystems that upgrade job seeker journey experience end to end
- Coach Machine Learning Engineers and Data Scientists on the Journey team to improve their performance, advise them on their career direction, and develop their qualifications.
- Work to understand, prioritize, and plan the team's work items without external guidance.
Tasks you're prepared for
(15 of 16 for Data Scientists)
- Analyze, manipulate, or process large sets of data using statistical software.
-
Apply feature selection algorithms to models predicting outcomes of interest, such as sales, attrition, and healthcare use.
via CSCD 484
- Apply sampling techniques to determine groups to be surveyed or use complete enumeration methods.
- Clean and manipulate raw data using statistical software.
- Compare models using statistical performance metrics, such as loss functions or proportion of explained variance.
+10 more covered tasks
Tasks you'd need to develop
(1)
Recommend data-driven solutions to key stakeholders.
These could be filled by an applied project, elective, or internship — see the program page for examples.
15/16
tasks
Machine Learning Engineer
FlightSafety International Inc
Seattle, WA
2026-06-03
Company Overview Docusign brings agreements to life. Over 1.5 million customers and more than a billion people in over 180 countries use Docusign solutions to accelerate the process of doing business and simplify people's lives. With intelligent agreement management, Docusign unleashes business-cr
What you'd do
- 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… 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
Nice to have
- 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
Tasks you're prepared for
(15 of 16 for Data Scientists)
- Analyze, manipulate, or process large sets of data using statistical software.
-
Apply feature selection algorithms to models predicting outcomes of interest, such as sales, attrition, and healthcare use.
via CSCD 484
- Apply sampling techniques to determine groups to be surveyed or use complete enumeration methods.
- Clean and manipulate raw data using statistical software.
- Compare models using statistical performance metrics, such as loss functions or proportion of explained variance.
+10 more covered tasks
Tasks you'd need to develop
(1)
Recommend data-driven solutions to key stakeholders.
These could be filled by an applied project, elective, or internship — see the program page for examples.
15/16
tasks
Principal Machine Learning Engineer
Oracle
Salem, OR
2026-06-03
Job Description At Oracle Cloud Infrastructure (OCI), we build the future of the cloud for Enterprises as a diverse team of fellow creators and inventors. We act with the speed and attitude of a start-up, with the scale and customer-focus of the leading enterprise software company in the world
Requirements
- BS/MS in Computer Science or equivalent experience
- 6-10+ years building and shipping enterprise distributed or cloud-native systems
- Experience scaling heterogeneous CPU/GPU training infrastructure for large multimodal frontier models
- Strong foundation in system design, distributed systems, and cloud architecture best practices
What you'd do
- At Oracle Cloud Infrastructure (OCI), we build the future of the cloud for Enterprises as a diverse team of fellow creators and inventors. We act with the speed and attitude of a start-up, with the sc… At Oracle Cloud Infrastructure (OCI), we build the future of the cloud for Enterprises as a diverse team of fellow creators and inventors. We act with the speed and attitude of a start-up, with the scale and customer-focus of the leading enterprise software company in the world.
- Values are OCI's foundation and how we deliver excellence. We strive for equity, inclusion, and respect for all. We are committed to the greater good in our products and our actions. We are constantly… Values are OCI's foundation and how we deliver excellence. We strive for equity, inclusion, and respect for all. We are committed to the greater good in our products and our actions. We are constantly learning and taking opportunities to grow our careers and ourselves. We challenge each other to stretch beyond our past to build our future.
- You are the builder here. You will be part of a team of smart, motivated, and diverse people and given the autonomy and support to do your best work. It is a dynamic and flexible workplace where you'l… You are the builder here. You will be part of a team of smart, motivated, and diverse people and given the autonomy and support to do your best work. It is a dynamic and flexible workplace where you'll belong and be encouraged.
- In? OCI ? AI Infrastructure ?org we are addressing exciting challenges at the intersection of artificial intelligence and cutting-edge cloud infrastructure. In this role, you will drive building state… In? OCI ? AI Infrastructure ?org we are addressing exciting challenges at the intersection of artificial intelligence and cutting-edge cloud infrastructure. In this role, you will drive building state-of-the-art training infrastructure for massive GPU clusters, as well as designing agentic systems deployed on OCI infrastructure at enterprise-scale. You will be innovating on leading principles of agentic software development and driving the frontier on infrastructure that maximizes the potential of bleeding-edge GPU clusters.
Nice to have
- Production experience with Cloud and ML technologies
- Experience working in the below areas and algorithms will be ideal but not mandatory:?
- Generative AI Modeling: Customizing LLM's, build and deploy LLM's at scale for large scale data generation
- Algorithms: Transformer models, Attention mechanism, Prompt tooling
Tasks you're prepared for
(15 of 16 for Data Scientists)
- Analyze, manipulate, or process large sets of data using statistical software.
-
Apply feature selection algorithms to models predicting outcomes of interest, such as sales, attrition, and healthcare use.
via CSCD 484
- Apply sampling techniques to determine groups to be surveyed or use complete enumeration methods.
- Clean and manipulate raw data using statistical software.
- Compare models using statistical performance metrics, such as loss functions or proportion of explained variance.
+10 more covered tasks
Tasks you'd need to develop
(1)
Recommend data-driven solutions to key stakeholders.
These could be filled by an applied project, elective, or internship — see the program page for examples.
15/16
tasks
Staff Machine Learning Engineer
Micron Technology, Inc.
Boise, ID
2026-06-03
Our vision is to transform how the world uses information to enrich life for _all_ . Micron Technology is a world leader in innovating memory and storage solutions that accelerate the transformation of information into intelligence, inspiring the world to learn, communicate and adva
Tasks you're prepared for
(15 of 16 for Data Scientists)
- Analyze, manipulate, or process large sets of data using statistical software.
-
Apply feature selection algorithms to models predicting outcomes of interest, such as sales, attrition, and healthcare use.
via CSCD 484
- Apply sampling techniques to determine groups to be surveyed or use complete enumeration methods.
- Clean and manipulate raw data using statistical software.
- Compare models using statistical performance metrics, such as loss functions or proportion of explained variance.
+10 more covered tasks
Tasks you'd need to develop
(1)
Recommend data-driven solutions to key stakeholders.
These could be filled by an applied project, elective, or internship — see the program page for examples.
15/16
tasks
Staff Data Scientist
Micron Technology, Inc.
Boise, ID
2026-06-03
Our vision is to transform how the world uses information to enrich life for _all_ . Micron Technology is a world leader in innovating memory and storage solutions that accelerate the transformation of information into intelligence, inspiring the world to learn, communicate and adva
Requirements
- Bachelor's degree in Data Science, Computer Science, Statistics, Mathematics, Engineering, Finance, Economics, or a related quantitative field, plus 5+ years of experience in data science, machine lea… Bachelor's degree in Data Science, Computer Science, Statistics, Mathematics, Engineering, Finance, Economics, or a related quantitative field, plus 5+ years of experience in data science, machine learning, or advanced analytics roles.
- Strong proficiency in Python and SQL, with hands-on experience developing, testing, and deploying predictive or statistical models on large, complex datasets.
- Working knowledge of core data science and AI/ML tools, including Python libraries such as pandas, NumPy, and scikit-learn, with hands-on experience in Snowflake, Streamlit, and modern AI/ML development environments.
- Experience working with Finance-related data, workflows, and business needs, including corporate finance, P&L, and manufacturing cost data, as well as forecasting, variance analysis, scenario planning… Experience working with Finance-related data, workflows, and business needs, including corporate finance, P&L, and manufacturing cost data, as well as forecasting, variance analysis, scenario planning, actuals-to-forecast reconciliation, or financial waterfall reporting.
What you'd do
- Lead the development of predictive models for finance use cases, including:
- Forecasting (revenue, expenses, cost drivers)
- Variance analysis (actuals vs. plan, drivers of deviation)
- Scenario modeling and sensitivity analysis to support business planning
Nice to have
- Advanced degree (Master's or PhD) in Data Science, Computer Science, Statistics, Mathematics, Operations Research, Finance, Economics, or a related quantitative discipline.
- Experience applying advanced machine learning, time series modeling, optimization, or AI techniques to Finance-related data, workflows, and business needs, including corporate finance, P&L, manufactur… Experience applying advanced machine learning, time series modeling, optimization, or AI techniques to Finance-related data, workflows, and business needs, including corporate finance, P&L, manufacturing cost data, forecasting, scenario modeling, driver analysis, or decision support.
- Hands-on experience developing, deploying, and monitoring conversational AI agents or LLM-based solutions in Snowflake, cloud, or similar enterprise data environments, including prompt/instruction des… Hands-on experience developing, deploying, and monitoring conversational AI agents or LLM-based solutions in Snowflake, cloud, or similar enterprise data environments, including prompt/instruction design, evaluation, and performance optimization.
- Experience translating finance business logic into production-grade analytical applications, model features, prompts, rules, or agent workflows that support scalable decision-making.
Tasks you're prepared for
(15 of 16 for Data Scientists)
- Analyze, manipulate, or process large sets of data using statistical software.
-
Apply feature selection algorithms to models predicting outcomes of interest, such as sales, attrition, and healthcare use.
via CSCD 484
- Apply sampling techniques to determine groups to be surveyed or use complete enumeration methods.
- Clean and manipulate raw data using statistical software.
- Compare models using statistical performance metrics, such as loss functions or proportion of explained variance.
+10 more covered tasks
Tasks you'd need to develop
(1)
Recommend data-driven solutions to key stakeholders.
These could be filled by an applied project, elective, or internship — see the program page for examples.
15/16
tasks
Senior Machine Learning Engineer
Indeed
Boise, ID
2026-06-03
Our Mission As the world's number 1 job site*, our mission is to help people get jobs. We strive to cultivate an inclusive and accessible workplace where all people feel comfortable being themselves. We're looking to grow our teams with more people who share our enthusiasm for innovation and c
What you'd do
- As a Senior Machine Learning Engineer on our Sourcing team, you will work on developing and deploying ML and AI solutions in production. You'll be collaborating with a cross-functional product team to… As a Senior Machine Learning Engineer on our Sourcing team, you will work on developing and deploying ML and AI solutions in production. You'll be collaborating with a cross-functional product team to drive value and better customer experiences for our Sourcing product, which connects employers with new talent through AI. This Senior MLE will help us improve our automated outreach quality, building new agentic experiences, and LLMOps reliability and infrastructure.
- Autonomously deliver ML and AI projects, including prompt development and evaluation, training ML models, building LLM-as-a-Judge capabilities, and building recommendation / ranking systems
- Develop LLM and machine learning model improvements, scale them in production, and run iterative A/B tests to improve our Sourcing product
- Estimate potential business impact of AI and ML and balance tradeoffs between delivery velocity and systematic infrastructure investments
Tasks you're prepared for
(15 of 16 for Data Scientists)
- Analyze, manipulate, or process large sets of data using statistical software.
-
Apply feature selection algorithms to models predicting outcomes of interest, such as sales, attrition, and healthcare use.
via CSCD 484
- Apply sampling techniques to determine groups to be surveyed or use complete enumeration methods.
- Clean and manipulate raw data using statistical software.
- Compare models using statistical performance metrics, such as loss functions or proportion of explained variance.
+10 more covered tasks
Tasks you'd need to develop
(1)
Recommend data-driven solutions to key stakeholders.
These could be filled by an applied project, elective, or internship — see the program page for examples.
15/16
tasks
Principal Machine Learning Engineer
Oracle
Boise, ID
2026-06-03
Job Description At Oracle Cloud Infrastructure (OCI), we build the future of the cloud for Enterprises as a diverse team of fellow creators and inventors. We act with the speed and attitude of a start-up, with the scale and customer-focus of the leading enterprise software company in the world
Requirements
- BS/MS in Computer Science or equivalent experience
- 6-10+ years building and shipping enterprise distributed or cloud-native systems
- Experience scaling heterogeneous CPU/GPU training infrastructure for large multimodal frontier models
- Strong foundation in system design, distributed systems, and cloud architecture best practices
What you'd do
- At Oracle Cloud Infrastructure (OCI), we build the future of the cloud for Enterprises as a diverse team of fellow creators and inventors. We act with the speed and attitude of a start-up, with the sc… At Oracle Cloud Infrastructure (OCI), we build the future of the cloud for Enterprises as a diverse team of fellow creators and inventors. We act with the speed and attitude of a start-up, with the scale and customer-focus of the leading enterprise software company in the world.
- Values are OCI's foundation and how we deliver excellence. We strive for equity, inclusion, and respect for all. We are committed to the greater good in our products and our actions. We are constantly… Values are OCI's foundation and how we deliver excellence. We strive for equity, inclusion, and respect for all. We are committed to the greater good in our products and our actions. We are constantly learning and taking opportunities to grow our careers and ourselves. We challenge each other to stretch beyond our past to build our future.
- You are the builder here. You will be part of a team of smart, motivated, and diverse people and given the autonomy and support to do your best work. It is a dynamic and flexible workplace where you'l… You are the builder here. You will be part of a team of smart, motivated, and diverse people and given the autonomy and support to do your best work. It is a dynamic and flexible workplace where you'll belong and be encouraged.
- In? OCI ? AI Infrastructure ?org we are addressing exciting challenges at the intersection of artificial intelligence and cutting-edge cloud infrastructure. In this role, you will drive building state… In? OCI ? AI Infrastructure ?org we are addressing exciting challenges at the intersection of artificial intelligence and cutting-edge cloud infrastructure. In this role, you will drive building state-of-the-art training infrastructure for massive GPU clusters, as well as designing agentic systems deployed on OCI infrastructure at enterprise-scale. You will be innovating on leading principles of agentic software development and driving the frontier on infrastructure that maximizes the potential of bleeding-edge GPU clusters.
Nice to have
- Production experience with Cloud and ML technologies
- Experience working in the below areas and algorithms will be ideal but not mandatory:?
- Generative AI Modeling: Customizing LLM's, build and deploy LLM's at scale for large scale data generation
- Algorithms: Transformer models, Attention mechanism, Prompt tooling
Tasks you're prepared for
(15 of 16 for Data Scientists)
- Analyze, manipulate, or process large sets of data using statistical software.
-
Apply feature selection algorithms to models predicting outcomes of interest, such as sales, attrition, and healthcare use.
via CSCD 484
- Apply sampling techniques to determine groups to be surveyed or use complete enumeration methods.
- Clean and manipulate raw data using statistical software.
- Compare models using statistical performance metrics, such as loss functions or proportion of explained variance.
+10 more covered tasks
Tasks you'd need to develop
(1)
Recommend data-driven solutions to key stakeholders.
These could be filled by an applied project, elective, or internship — see the program page for examples.
15/16
tasks
Machine Learning Engineering Manager
Indeed
Boise, ID
2026-06-03
Our Mission As the world's number 1 job site*, our mission is to help people get jobs. We strive to cultivate an inclusive and accessible workplace where all people feel comfortable being themselves. We're looking to grow our teams with more people who share our enthusiasm for innovation and c
What you'd do
- At Indeed, we are committed to delivering exceptional experiences that connect job seekers with opportunities through innovative technology. We integrate machine learning at every step to create consi… At Indeed, we are committed to delivering exceptional experiences that connect job seekers with opportunities through innovative technology. We integrate machine learning at every step to create consistent, engaging, and secure experiences that meet the needs of our users. Our teams consist of Software Engineers, UX Designers, Product Managers, and Machine Learning professionals collaborating across regions to drive impactful business outcomes.
- As a Machine Learning Engineering Manager, you will onboard and oversee junior scientists and technical leads, partnering closely with Product, Software Engineering, and UX teams. Your focus will incl… As a Machine Learning Engineering Manager, you will onboard and oversee junior scientists and technical leads, partnering closely with Product, Software Engineering, and UX teams. Your focus will include developing and innovating machine learning ecosystems that upgrade job seeker journey experience end to end
- Coach Machine Learning Engineers and Data Scientists on the Journey team to improve their performance, advise them on their career direction, and develop their qualifications.
- Work to understand, prioritize, and plan the team's work items without external guidance.
Tasks you're prepared for
(15 of 16 for Data Scientists)
- Analyze, manipulate, or process large sets of data using statistical software.
-
Apply feature selection algorithms to models predicting outcomes of interest, such as sales, attrition, and healthcare use.
via CSCD 484
- Apply sampling techniques to determine groups to be surveyed or use complete enumeration methods.
- Clean and manipulate raw data using statistical software.
- Compare models using statistical performance metrics, such as loss functions or proportion of explained variance.
+10 more covered tasks
Tasks you'd need to develop
(1)
Recommend data-driven solutions to key stakeholders.
These could be filled by an applied project, elective, or internship — see the program page for examples.
15/16
tasks
Senior Machine Learning Engineer
Indeed
Seattle, WA
2026-06-03
Our Mission As the world's number 1 job site*, our mission is to help people get jobs. We strive to cultivate an inclusive and accessible workplace where all people feel comfortable being themselves. We're looking to grow our teams with more people who share our enthusiasm for innovation and c
What you'd do
- As a Senior Machine Learning Engineer on our Sourcing team, you will work on developing and deploying ML and AI solutions in production. You'll be collaborating with a cross-functional product team to… As a Senior Machine Learning Engineer on our Sourcing team, you will work on developing and deploying ML and AI solutions in production. You'll be collaborating with a cross-functional product team to drive value and better customer experiences for our Sourcing product, which connects employers with new talent through AI. This Senior MLE will help us improve our automated outreach quality, building new agentic experiences, and LLMOps reliability and infrastructure.
- Autonomously deliver ML and AI projects, including prompt development and evaluation, training ML models, building LLM-as-a-Judge capabilities, and building recommendation / ranking systems
- Develop LLM and machine learning model improvements, scale them in production, and run iterative A/B tests to improve our Sourcing product
- Estimate potential business impact of AI and ML and balance tradeoffs between delivery velocity and systematic infrastructure investments
Tasks you're prepared for
(15 of 16 for Data Scientists)
- Analyze, manipulate, or process large sets of data using statistical software.
-
Apply feature selection algorithms to models predicting outcomes of interest, such as sales, attrition, and healthcare use.
via CSCD 484
- Apply sampling techniques to determine groups to be surveyed or use complete enumeration methods.
- Clean and manipulate raw data using statistical software.
- Compare models using statistical performance metrics, such as loss functions or proportion of explained variance.
+10 more covered tasks
Tasks you'd need to develop
(1)
Recommend data-driven solutions to key stakeholders.
These could be filled by an applied project, elective, or internship — see the program page for examples.