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Data Scientists

15-2051.00 Bright Outlook $158K
77
postings · Master's
Career stage: All Intern (18) Entry-level (23) Mid-level (447) Senior (713) Manager (182) Director (151)
Education: All Bachelor's (52) Master's (77) Doctorate (149)
What do these filters mean?
Career stage is read from the job title. Use it to find jobs aimed at where you are right now:
  • Intern You can apply while still in school.
  • Entry-level Designed for new graduates.
  • Mid-level Typically expects internship or 2-3 years of experience.
  • Senior Established career role — usually 5+ years experience.
  • Manager Leads a team of engineers, not an early-career role.
  • Director Executive role — typically 10+ years of career experience.
Education is the highest degree the posting explicitly mentions. Postings that don't say are not filtered out — they appear under "All".
(USA) Senior, Data Scientist
Walmart · Bellevue, WA
Senior Master's
2026-06-05
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
  • Experience with big data analytics - identifying trends, patterns, and outliers in large volumes of data
  • Strong Experience in Python with excellent knowledge of Data Structures
  • Strong Experience with big data platforms - Hadoop (Hive, Pig, Map Reduce, HQL, Scala, Spark)
  • Hands on experience with Git
  • Experience with SQL and relational databases, data warehouse
  • Bachelors with > 7 years of experience / Master's degree with > 5 years of experience. Educational qualifications should be preferably in Computer Science/Mathematics/Statistics or a related area. Experience should be relevant to the role.
  • Experience in ecommerce domain.
  • Experience in R and Julia
  • Demonstrated success in data science platforms like Kaggle.
  • _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 3 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 1 years' experience in an analytics related field. Option 3 - 5 years' experience in an analytics or related field.
Preferred
  • _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, 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
  • Walmart and its subsidiaries are committed to maintaining a drug-free workplace and has a no tolerance policy regarding the use of illegal drugs and alcohol on the job. This policy applies to all employees and aims to create a safe and productive work environment.
Responsibilities
  • *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
  • Build and train statistical models and machine learning algorithms for replication for future projects
  • Communicate recommendations to business partners and influencing future plans based on insights
View full posting on CareerOneStop → ID: 2b56f54b6ce5
Data Scientist, Fleet Planning , Global Fleet Products
Amazon · Bellevue, WA
Mid-level Master's
2026-06-05
Requirements
  • 5+ years of data querying languages (e.g. SQL), scripting languages (e.g. Python) or statistical/mathematical software (e.g. R, SAS, Matlab, etc.) experience
  • Master's degree in operations research, applied mathematics, theoretical computer science, or equivalent, or a Associate's degree or above and experience investigating the feasibility of applying scientific principles and concepts to business problems and products
Preferred
  • 2+ years of data visualization using AWS QuickSight, Tableau, R Shiny, etc. experience
  • Experience managing data pipelines
  • Experience as a leader and mentor on a data science team
Responsibilities
  • Build models and automation for planners for generating vehicle allocation plans
  • Partner with program teams to test and measure success of implemented model
  • Lead reviews with senior leadership, deep dive model outputs and explain implications of model recommendations.
View full posting on CareerOneStop → ID: b1b087e9e938
EY-Parthenon - Strategy and Execution - Growth Platforms - AI/ML Engineer - Sr Associate/Consultant
EY · Seattle, WA
Senior Master's
2026-06-05
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.
  • Strong understanding of ML workflow including ingesting, analyzing, transforming data, and evaluating results to make meaningful predictions.
  • Fluency in Python, PyTorch or TensorFlow, with ability to architect APIs around ML models.
  • Demonstrated experience designing, building, and maintaining ML models, frameworks, and pipelines.
  • Excellent communication skills, with the ability to convey complex, technical concepts and progress, methodologies, solutioning, and results to business and client stakeholders.
  • The ability and willingness to travel and work in excess of standard hours when necessary.
  • *Ideally, you will have
  • Experience building and deploying AI/ML products or features in a production environment.
  • Experience working in a startup and/or management/strategy consulting.
  • Knowledge of how to leverage AI tools in a business setting, including Microsoft Copilot.
  • Collaborative, problem-solving, and growth-oriented mindset.
  • *What we look fo
  • We're interested in passionate leaders with strong vision and a desire to stay on top of trends in the Data Science and Big Data industry. If you have a genuine passion for helping businesses achieve the full potential of their data, this role is for you.
Responsibilities
  • 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.
  • Participate in model selection, feature design, embedding strategy, and prompt frameworks (e.g., LangChain, LlamaIndex).
  • Participate in the design and build robust data pipelines that are scalable, reproducible, and versioned.
View full posting on CareerOneStop → ID: e0e3ba039dcc
EY-Parthenon - Strategy and Execution - Growth Platforms - Data Scientist - Sr Associate/Consultant
EY · Seattle, WA
Senior Master's
2026-06-05
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).
  • Experience with merging and reconciling third-party data (public APIs, vendor flat files, dashboards).
  • Comfort defining semantic layers and mapping unstructured/dirty datasets into usable models for AI/BI use.
  • Basic understanding of ML/feature pipelines and downstream modeling needs.
  • The ability and willingness to travel and work in excess of standard hours when necessary.
  • *Ideally, you will have
  • Experience working in a startup and/or management/strategy consulting.
  • Knowledge of how to leverage AI tools in a business setting, including Microsoft Copilot.
  • Collaborative, problem-solving, and growth-oriented mindset.
  • *What we look fo
  • We're interested in passionate leaders with strong vision and a desire to stay on top of trends in the Data Science and Big Data industry. If you have a genuine passion for helping businesses achieve the full potential of their data, this role is for you.
Responsibilities
  • 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.
  • Design normalization and joining pipelines across vertical domains (insurance + consumer + economic data).
  • Build data access layers optimized for ML (feature stores, event streams, vector stores).
  • Define and enforce standards for data provenance, quality checks, logging, and version control.
  • Partner with AI/ML and Platform teams to ensure data is ML- and privacy-ready (HIPAA, SOC2, etc.).
View full posting on CareerOneStop → ID: 37cb20019308
Machine Learning Research Engineer , Text Generation, Input Experience
Apple · Seattle, WA
Mid-level Master's
2026-06-05
Requirements
  • Strong machine learning fundamentals
  • Knowledge of ML techniques such as implementing basic optimizers, applying parameter tuning in model training and evaluation, and reproducing research experiments
  • Strong programming and communication skills
  • Ph. D. in CS/EE/Physics/Statistics/etc. (or Masters with 4 years of proven experience)
Preferred
  • Familiar with model compression algorithms including quantization, pruning, distillations, and experience optimizing large diffusion models or language models
  • Experience with hardware architecture, software & hardware co-design
  • Experience with deploying large ML models in real world products
  • Actively programming with high-quality codes across complex and large repositories
  • Familiar with common NLP algorithms and applications, including tokenization, language modeling, text decoding, text classifier etc
  • Experience of multi-modal modeling, presenting plans, progress, and results or demos regularly and concisely
Responsibilities
  • Apple is where individual imaginations gather together, committing to the values that lead to great work. Every new product we build or service we create, what we deliver is the result of us making each other's ideas stronger. It's the diversity of our people and their thinking that inspires the innovation that runs through everything we do. When we bring everybody in, we can do the best work of our lives. Here, you'll do more than join something - you'll add something. Text generation is a key enabler for accelerated text input and intelligent interaction on Apple platforms.
  • Our team is working on redefining user interaction with generative models for text generation. If you want to be part of an ambitious, organized and collaborative team that ships user experiences with pioneering ML, partnered with the best UI designs, come join the Input Experience NLP team. Our work has been highlighted in multiple WWDC keynotes including Intelligent Input in 2023, Writing Tools and Smart Reply in 2024!
  • We exemplify Apple's outstanding integration of hardware and software to create seamless input experiences. You will have the opportunity to go from building offline pioneering NLP models to optimization of the models for different hardware backends and user interfaces that make the experience magical. Our vision always includes a deep dedication to strengthening Apple's privacy policy by achieving all of the above on device with powerful Machine Learning.
  • As a key pillar of Apple Intelligence, input experience will be the main area where you bring impact to billions of users with your Machine Learning expertise, engineering passion, and programming skills. You will work with a hard-working and dedicated set of outstanding ML and software engineers on a wide range of most advanced text generation technologies such as context-augmented text rewriting, safety-controlled text composition, free-form text transformation, personalized smart interactions, etc.
  • Our team has been working in this area for years and own the NLP and ML text input stack for the keyboard input that includes auto correction, predictive typing on all Apple platforms. We also work on full stack ML applied to NLP and expose these key technologies across Apple on device and also to third party applications through the Natural-Language framework. If you want to amplify your strong Machine Learning and NLP skills into user experiences that will reach every person around you, this is the perfect opportunity!
View full posting on CareerOneStop → ID: c6cfd50d8ceb
AI and Data Science Engineer II
Deloitte · Seattle, WA
Mid-level Master's
2026-06-04
Requirements
  • Bachelor's degree in engineering, mathematics, physics, machine learning, statistics, computer science, or another quantitative field
  • 2+ years of industry experience outside of academia applying data science or machine learning methods
  • Experience translating business goals into machine learning use cases and model design
  • Experience performing exploratory data analysis and developing predictive models
  • Ability to travel 30%, on average, based on the work you do and the clients and industries/sectors you serve.
  • Must be legally authorized to work in the United States without the need for employer sponsorship, now or at any time in the future.
Preferred
  • Master's degree in engineering, mathematics, physics, machine learning, statistics, computer science, or another quantitative field
  • Experience manipulating large marketing data sets and performing extract, transform, and load activities
  • Experience with boosted trees, logistic regression, classification techniques, unsupervised models, large language models, or experimental design
  • Experience with data sets generated in advertising technology or marketing technology environments
  • Experience presenting complex data insights to non-technical audiences
  • Experience with deep learning architectures or reinforcement learning
  • The wage range for this role takes into account the wide range of factors that are considered in making compensation decisions including but not limited to skill sets; experience and training; licensure and certifications; and other business and organizational needs. The disclosed range estimate has not been adjusted for the applicable geographic differential associated with the location at which the position may be filled. At Deloitte, it is not typical for an individual to be hired at or near the top of the range for their role and compensation decisions are dependent on the facts and circumstances of each case. A reasonable estimate of the current range is $86,700 - $170,900.
  • You may also be eligible to participate in a discretionary annual incentive program, subject to the rules governing the program, whereby an award, if any, depends on various factors, including, without limitation, individual and organizational performance.
View full posting on CareerOneStop → ID: c205110ea9aa
Manager, Machine Learning Engineering - Ad Platforms
The Walt Disney Company · Seattle, WA
Manager Master's
2026-06-04
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.
  • Proven experience designing, building, and deploying scalable machine learning models and systems in production.
  • Experience deploying ML/GenAI systems at scale using cloud platforms and MLOps practices
  • Advanced programming proficiency (e.g., Python, Java, or similar); experience with ML/DL frameworks (e.g., TensorFlow, PyTorch, JAX, Hugging Face).
  • Experience building, fine-tuning, evaluating, and deploying LLM-based systems (e.g., RAG, prompt engineering, model optimization)
  • Demonstrated ability to lead global teams and collaborate across organizational boundaries.
Preferred
  • 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).
  • The hiring range for this position in Los Angeles, CA area is $171,600 - $230,100 per year and Seattle Area is $179,700 - $241,000. The base pay actually offered will take into account internal equity and also may vary depending on the candidate's geographic region, job-related knowledge, skills, and experience among other factors. A bonus and/or long-term incentive units may be provided as part of the compensation package, in addition to the full range of medical, financial, and/or other benefits, dependent on the level and position offered.
  • *Job ID: 10152782
Responsibilities
  • 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.
  • A proven ability to work with product teams to translate requirements into
  • well-defined technical implementations, as well as the ability to define technical and operational metrics to measure system health.
  • A keen eye for potential optimizations and enhancements.
  • Kindness and pragmatic optimism.
  • A deep understanding of model development cycles and AI tool usage
  • Lead, mentor and guide Data Scientists, Machine Learning and AI engineers to build solutions adhering to industry best practices and deliver scalable solutions including model architecture and algorithm selection.
  • Lead by example and always strive to improve the design for more scalable, cleaner, and decoupled implementations.
  • Drive adoption of best practices in model development, code quality, testing, and documentation.
  • Solid understanding and usage of automated tools (AI) while adhering to company policy.
  • Define strategic direction for machine learning projects and collaborate with product and engineering stakeholders.
  • Oversee end-2-end machine learning workflow, including data collection, model development, deployment and modeling. These are expected to be aligned with the larger platform strategy and tools in collaboration with the global teams to stay consistent across Ad Platforms.
  • Foster innovation by exploring new ML techniques, tools, and technologies.
  • Communicate strategies, progress, and results to leadership and cross-functional teams.
  • Ensure responsible AI practices, including fairness, explainability, and compliance with privacy and ethical standards.
  • Develop partnerships across the organization to identify and prioritize high-impact ML opportunities.
  • Available for On-Call rotations based on the team's escalation policy and support schedule for ML/AI solutions
View full posting on CareerOneStop → ID: 0f8ff097436c
Senior Machine Learning Engineering Manager, Ad Platforms
The Walt Disney Company · Seattle, WA
Manager Master's
2026-06-04
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.
  • Experience deploying ML/GenAI systems at scale using cloud platforms and MLOps practices
  • Advanced programming proficiency (e.g., Python, Java, or similar); experience with ML/DL frameworks (e.g., TensorFlow, PyTorch, JAX, Hugging Face).
  • Experience building, fine-tuning, evaluating, and deploying LLM-based systems (e.g., RAG, prompt engineering, model optimization)
  • Demonstrated ability to lead global teams and collaborate across organizational boundaries.
Preferred
  • 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).
  • The hiring range for this position in Los Angeles, CA area is $207,400 - $278,100 per year and Seattle Area is $217,300 - $291,500. The base pay actually offered will take into account internal equity and also may vary depending on the candidate's geographic region, job-related knowledge, skills, and experience among other factors. A bonus and/or long-term incentive units may be provided as part of the compensation package, in addition to the full range of medical, financial, and/or other benefits, dependent on the level and position offered.
  • *Job ID: 10152780
Responsibilities
  • 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.
  • A proven ability to work with product teams to translate requirements into
  • well-defined technical implementations, as well as the ability to define technical and operational metrics to measure system health.
  • A keen eye for potential optimizations and enhancements.
  • Kindness and pragmatic optimism.
  • A deep understanding of model development cycles and AI tool usage
  • Lead, mentor and guide senior individual contributors and managers across data scientists, machine learning and AI engineers teams to build solutions adhering to industry best practices and deliver scalable solutions including model architecture and algorithm selection.
  • Define strategic direction for machine learning projects and collaborate with product and engineering stakeholders.
  • Lead by example and always strive to improve the design for more scalable, cleaner, and decoupled implementations.
  • Drive adoption of best practices in model development, code quality, testing, and documentation.
  • Solid understanding and usage of automated tools (AI) while adhering to company policy.
  • Oversee end-2-end machine learning workflow, including data collection, model development, deployment and modeling. These are expected to be aligned with the larger platform strategy and tools in collaboration with the global teams to stay consistent across Ad Platforms.
  • Foster innovation by exploring new ML techniques, tools, and technologies.
  • Communicate strategies, progress, and results to leadership and cross-functional teams.
  • Ensure responsible AI practices, including fairness, explainability, and compliance with privacy and ethical standards.
  • Develop partnerships across the organization to identify and prioritize high-impact ML opportunities.
  • Available for On-Call rotations based on the team's escalation policy and support schedule for ML/AI solutions
View full posting on CareerOneStop → ID: f33cab28b6a2
Staff Machine Learning Engineer - News, Books, and Stocks Team
Apple · Seattle, WA
Senior Master's
2026-06-04
Requirements
  • MS in Machine Learning, Computer Science, or related field. Alternatively, equivalent industry experience to an MS degree is acceptable.
  • At least 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.
  • Experience with recommender systems.
  • Experience with text-centric AI/ML (LLMs, document classification, search, etc.)
  • Experience delivering high quality software at scale.
  • Ability to communicate effectively and collaborate with partner teams.
  • Commitment to encouraging an open and inclusive work environment.
Preferred
  • Experience in a technical leadership role.
Responsibilities
  • In a time where the news and book media landscapes are changing by the day, Apple News and
  • Apple Books stand as champions of quality content, expert curation, user privacy, and the
  • judicious use of machine learning.
  • Our lively and brilliant team consists of client and machine learning engineers who embody
  • Apple's values. We inspire, teach, and otherwise enable each other to do the best work of ou
  • Our team's outstanding retention rate speaks to our strong culture of respect for our teammates
  • as both engineers and people.
  • Would you like to work on such a team, solving hard problems in machine learning? Terrific!
  • Please join us for the next generation of these apps!
  • Our team is seeking a high-energy and self-driven machine learning engineer who will play a
  • central role in the delivery of scalable services. The team uses machine learning to tackle
  • difficult and complicated problems in the news, books, and stocks domains, including text
  • extraction, named entity recognition, duplicate detection, search, ranking, and much more! As a
  • member of our dynamic group, you'll have the rare and rewarding opportunity to craft upcoming
  • products that will delight and encourage millions of Apple's customers every day!
View full posting on CareerOneStop → ID: 056dfeed4396
Principal Machine Learning Engineer
Oracle · Olympia, WA
Senior Master's
2026-06-03
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
  • Proficiency in Java, Python, or similar object-oriented languages
  • Experience building highly available services using service-oriented design patterns and service-to-service communication protocols
  • Proven ability to deliver impact in collaborative, fast-paced environments
  • Strong verbal and written communication skills, including technical design documentation
  • Hands-on experience with containers and orchestration technologies such as Kubernetes and Docke
Preferred
  • 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
Responsibilities
  • 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 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'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-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.
  • We are working at the forefront of Generative AI (GenAI) landscape working with teams across Oracle on multi-modal data generation and leading the framework across Oracle.
  • Design and develop AI software in Java, Python, and other languages.?
  • Participate in the entire software lifecycle - development, testing, CI/CD and production operations
  • Participate in the entire model development cycle - training, fine-tuning, model serving, evaluation/benchmarking and human preference learning.
  • Apply engineering principles for defining robust and maintainable architectures and designs.?
  • Build cloud service on top of the modern Infrastructure as Service (IaaS) building blocks at OCI
  • Design and build distributed, scalable, fault tolerant software systems to facilitate development of GenAI models.
  • Identify requirements, scope solutions, estimate work, schedule deliverables. Help establish and drive the adoption of outstanding coding standards and patterns and help enhance our inclusive engineering culture.
  • Contribute to publications, blogs and open-source ML performance submissions partnering with product managers
  • Balance between product feature development and production operational concerns like ops automation, structured logging, instrumentation for metrics and participating in on-call.
View full posting on CareerOneStop → ID: 5fada611e570
Principal Machine Learning Engineer
Oracle · Boise, ID
Senior Master's
2026-06-03
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
  • Proficiency in Java, Python, or similar object-oriented languages
  • Experience building highly available services using service-oriented design patterns and service-to-service communication protocols
  • Proven ability to deliver impact in collaborative, fast-paced environments
  • Strong verbal and written communication skills, including technical design documentation
  • Hands-on experience with containers and orchestration technologies such as Kubernetes and Docke
Preferred
  • 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
Responsibilities
  • 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 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'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-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.
  • We are working at the forefront of Generative AI (GenAI) landscape working with teams across Oracle on multi-modal data generation and leading the framework across Oracle.
  • Design and develop AI software in Java, Python, and other languages.?
  • Participate in the entire software lifecycle - development, testing, CI/CD and production operations
  • Participate in the entire model development cycle - training, fine-tuning, model serving, evaluation/benchmarking and human preference learning.
  • Apply engineering principles for defining robust and maintainable architectures and designs.?
  • Build cloud service on top of the modern Infrastructure as Service (IaaS) building blocks at OCI
  • Design and build distributed, scalable, fault tolerant software systems to facilitate development of GenAI models.
  • Identify requirements, scope solutions, estimate work, schedule deliverables. Help establish and drive the adoption of outstanding coding standards and patterns and help enhance our inclusive engineering culture.
  • Contribute to publications, blogs and open-source ML performance submissions partnering with product managers
  • Balance between product feature development and production operational concerns like ops automation, structured logging, instrumentation for metrics and participating in on-call.
View full posting on CareerOneStop → ID: 59e51d431663
Staff Machine Learning Engineer
Micron Technology, Inc. · Boise, ID
Senior Master's
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

View full posting on CareerOneStop → ID: fc816a13d902
Principal Machine Learning Engineer
Oracle · Salem, OR
Senior Master's
2026-06-03
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
  • Proficiency in Java, Python, or similar object-oriented languages
  • Experience building highly available services using service-oriented design patterns and service-to-service communication protocols
  • Proven ability to deliver impact in collaborative, fast-paced environments
  • Strong verbal and written communication skills, including technical design documentation
  • Hands-on experience with containers and orchestration technologies such as Kubernetes and Docke
Preferred
  • 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
Responsibilities
  • 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 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'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-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.
  • We are working at the forefront of Generative AI (GenAI) landscape working with teams across Oracle on multi-modal data generation and leading the framework across Oracle.
  • Design and develop AI software in Java, Python, and other languages.?
  • Participate in the entire software lifecycle - development, testing, CI/CD and production operations
  • Participate in the entire model development cycle - training, fine-tuning, model serving, evaluation/benchmarking and human preference learning.
  • Apply engineering principles for defining robust and maintainable architectures and designs.?
  • Build cloud service on top of the modern Infrastructure as Service (IaaS) building blocks at OCI
  • Design and build distributed, scalable, fault tolerant software systems to facilitate development of GenAI models.
  • Identify requirements, scope solutions, estimate work, schedule deliverables. Help establish and drive the adoption of outstanding coding standards and patterns and help enhance our inclusive engineering culture.
  • Contribute to publications, blogs and open-source ML performance submissions partnering with product managers
  • Balance between product feature development and production operational concerns like ops automation, structured logging, instrumentation for metrics and participating in on-call.
View full posting on CareerOneStop → ID: 4b08e880772a
Principal Machine Learning Engineer
Oracle · Helena, MT
Senior Master's
2026-06-03
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
  • Proficiency in Java, Python, or similar object-oriented languages
  • Experience building highly available services using service-oriented design patterns and service-to-service communication protocols
  • Proven ability to deliver impact in collaborative, fast-paced environments
  • Strong verbal and written communication skills, including technical design documentation
  • Hands-on experience with containers and orchestration technologies such as Kubernetes and Docke
Preferred
  • 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
Responsibilities
  • 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 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'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-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.
  • We are working at the forefront of Generative AI (GenAI) landscape working with teams across Oracle on multi-modal data generation and leading the framework across Oracle.
  • Design and develop AI software in Java, Python, and other languages.?
  • Participate in the entire software lifecycle - development, testing, CI/CD and production operations
  • Participate in the entire model development cycle - training, fine-tuning, model serving, evaluation/benchmarking and human preference learning.
  • Apply engineering principles for defining robust and maintainable architectures and designs.?
  • Build cloud service on top of the modern Infrastructure as Service (IaaS) building blocks at OCI
  • Design and build distributed, scalable, fault tolerant software systems to facilitate development of GenAI models.
  • Identify requirements, scope solutions, estimate work, schedule deliverables. Help establish and drive the adoption of outstanding coding standards and patterns and help enhance our inclusive engineering culture.
  • Contribute to publications, blogs and open-source ML performance submissions partnering with product managers
  • Balance between product feature development and production operational concerns like ops automation, structured logging, instrumentation for metrics and participating in on-call.
View full posting on CareerOneStop → ID: dd11225a881e
Product Data Science Intern
FlightSafety International Inc · Seattle, WA
Intern Master's
2026-06-03
Responsibilities
  • Docusign's Product Data Science team is looking for a Data Scientist Intern to support the development of key data products and capabilities to enable data-driven product development and decision making. In this role, you would be part of the Product Data Science team and work directly in partnership with a variety of stakeholders including but not limited to Product, Engineering and User Experience partners to support and empower them with data-driven actionable insights. You will be embedded in specific product spaces requiring you to establish and grow relationships. As a Data Scientist Intern, you'll dig into the data to uncover insights, identify opportunities for product improvements and new product development, define product metrics with goals, design experiments and develop data science models to drive customer experience, engagement, and adoption of Docusign's products.
  • This role is not eligible for OPT or sponsorship now or in the future.
  • This position is an individual contributor role reporting to the Director, Product Data Science.
  • *Responsibility
  • Collaborate with cross-functional teams to research, build and improve data analysis to identify opportunities for product improvements, new product features, product utilization, and improve customer experience, engagement, and retention
  • Partner closely with the product managers, user researchers, engineers, and leadership to capture and prioritize potential insights, analysis, and data product opportunities that will drive maximum business impact
  • Leverage data to develop actionable analytical insights and present findings to senior management
  • Partner with Product teams to design, administer, and analyze the results of A/B and multivariate tests and other ML models
  • Design and build dashboards to provide actionable insights and key business metrics
  • Design, build and test reliable data pipelines to extract and transform data
  • Identify, design, and implement process improvements by automating manual processes for greater efficiency
  • Collaborate with stakeholders across organizations to support their data needs
  • Implement data quality checks to maintain the high quality of data
  • Optimize and maintain the existing pipelines
  • Document the work in confluence and Alation
  • Job Designation
  • *Hybrid: Employee divides their time between in-office and remote work. Access to an office location is required. (Frequency: Minimum 2 days per week; may vary by team but will be weekly in-office expectation)
View full posting on CareerOneStop → ID: 093d7411edef
Data Scientist
iSpot.tv, INC. · Bellevue, WA
Mid-level Master's
2026-06-02

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

View full posting on CareerOneStop → ID: 3c086ed88f3e
Finance Manager, Advertising Finance - Measurement, Ad Tech, and Data Science (MADS)
Amazon · Seattle, WA
Manager Master's
2026-05-30
Requirements
  • Bachelor's degree in Finance, Accounting, Business, Economics or a highly analytical field (e.g., Engineering, Math, and Computer Science)
  • 5+ years of finance or a related analytical field experience
  • Experience coordinating between technical teams, peers and business stakeholders
  • 5+ years of experience creating financial models and strategic analyses that support business decisions
Preferred
  • Experience in TM1, Data Warehouse and SQL
  • Experience with AI/ML technologies
  • Experience leading financial technology automation and process improvement initiatives with tech and non-tech teams
  • Advertising or Media experience is a plus
Responsibilities
  • Business Partnering & Performance Management
  • Serve as the finance partner for Performance Measurement and Infrastructure leadership
  • Advise engineering and product leaders on risks, opportunities, and trade-offs impacting quarterly and annual goals
  • Run weekly business reviews, define and report KPIs, and communicate financials to senior MADS leadership
  • Support monthly business reviews with insights, variance analysis, and recommendations
  • Strategic Analysis & Cost Management
  • Manage hardware cost analysis for Infrastructure, partnering with engineering on capacity planning and cost efficiency
  • Provide financial modeling and strategic analysis for PRFAQs, product roadmap decisions, and investment trade-offs
  • Deliver analyses that translate complex technical problems into actionable insights for senior leadership
  • Partner with BIE and analytics teams to build scalable dashboards and automated reporting
  • Cross-Functional Collaboration & Operational Excellence
  • Partner with product, engineering, data science, and sales teams to align strategy with business priorities
  • Collaborate across Advertising Finance to ensure consistency in planning and reporting
  • Leverage AI tools daily to raise the speed and quality of finance work, and build AI-powered solutions for the team
  • Drive process improvements that simplify and scale finance mechanisms, insisting on the highest standards in data accuracy and rigo
View full posting on CareerOneStop → ID: e9237370ca84
Staff Data Scientist, Product
Google · Seattle, WA
Senior Master's
2026-05-30
Requirements
  • Bachelor's degree in Statistics, Mathematics, Data Science, Engineering, Physics, Economics, or a related quantitative field.
  • 10 years of work experience using analytics to solve product or business problems, performing statistical analysis, and coding (e.g., Python, R, SQL) (or 8 years work experience plus a Master's degree).
Preferred
  • Master's degree in Statistics, Mathematics, Data Science, Engineering, Physics, Economics, or a related quantitative field.
  • 12 years of work experience using analytics to solve product or business problems, performing statistical analysis, and coding (e.g., Python, R, SQL).
Responsibilities
  • Help serve Google's worldwide user base of more than a billion people. Data Scientists provide quantitative support, market understanding and a strategic perspective to our partners throughout the organization. As a data-loving member of the team, you serve as an analytics expert for your partners, using numbers to help them make better decisions. You will weave stories with meaningful insight from data. You'll make critical recommendations for your fellow Googlers in Engineering and Product Management. You relish tallying up the numbers one minute and communicating your findings to a team leader the next.
  • Google is an engineering company at heart. We hire people with a broad set of technical skills who are ready to take on some of technology's greatest challenges and make an impact on users around the world. At Google, engineers not only revolutionize search, they routinely work on scalability and storage solutions, large-scale applications and entirely new platforms for developers around the world. From Google Ads to Chrome, Android to YouTube, social to local, Google engineers are changing the world one technological achievement after another.
  • The US base salary range for this full-time position is $192,000-$278,000 + bonus + equity + benefits. Our salary ranges are determined by role, level, and location. Within the range, individual pay is determined by work location and additional factors, including job-related skills, experience, and relevant education or training. Your recruiter can share more about the specific salary range for your preferred location during the hiring process.
  • Please note that the compensation details listed in US role postings reflect the base salary only, and do not include bonus, equity, or benefits. Learn more aboutbenefits at Google (https://careers.google.com/benefits/) .
  • Perform analysis utilizing relevant tools (e.g., SQL, R, Python). Provide analytical thought leadership through proactive and strategic contributions (e.g., suggests new analyses, infrastructure or experiments to drive improvements in the business).
  • Own outcomes for projects by covering problem definition, metrics development, data extraction and manipulation, visualization, creation, and implementation of analytical/statistical models, and presentation to stakeholders.
  • Develop solutions, lead, and manage problems that may be ambiguous and lacking clear precedent by framing problems, generating hypotheses, and making recommendations from a perspective that combines both, analytical and product-specific expertise.
  • Oversee the integration of cross-functional and cross-organizational project/process timelines, develop process improvements and recommendations, and help define operational goals and objectives.
  • Directly or indirectly oversee the contributions of others and develop colleagues' capabilities in the area of specialization.
  • Information collected and processed as part of your Google Careers profile, and any job applications you choose to submit is subject to Google'sApplicant and Candidate Privacy Policy (./privacy-policy) .
View full posting on CareerOneStop → ID: 6269f214431d
Principal Data Scientists
T-Mobile USA, Inc. · Bellevue, WA
Senior Master's
2026-05-29

T-Mobile USA, Inc. seeks Principal Data Scientists in Bellevue, WA to implement and maintain modeling pipelines in Python, ensuring statistical accuracy and version control in collaboration with data engineering teams (10%). Communicate complex findings clearly to technical and non-technical stakeho

View full posting on CareerOneStop → ID: 5d0ca1841abb
Data Scientist II, Middle Mile Transportation Science team
Amazon · Bellevue, WA
Mid-level Master's
2026-05-28
Requirements
  • Master's degree in Science, Technology, Engineering, or Mathematics (STEM)
  • 2+ years of data querying languages (e.g. SQL), scripting languages (e.g. Python) or statistical/mathematical software (e.g. R, SAS, Matlab, etc.) experience
  • 2+ years of machine learning/statistical modeling data analysis tools and techniques, and parameters that affect their performance experience
  • Experience with AWS services including S3, Redshift, Sagemaker, EMR, Kinesis, Lambda, and EC2
  • Proficiency in statistical modeling and machine learning - time-series forecasting, regression, tree-based methods, and deep learning.
  • Demonstrated ability to communicate technical results to non-technical business audiences.
Preferred
  • 3+ years of data querying languages (e.g. SQL), scripting languages (e.g. Python) or statistical/mathematical software (e.g. R, SAS, Matlab, etc.) experience
  • 3+ years of machine learning/statistical modeling data analysis tools and techniques, and parameters that affect their performance experience
Responsibilities
  • Design and implement complex ML and optimization solutions (forecasting, MIP/LP, simulation, Deep learning / foundation model);
  • Drive end-to-end delivery of scalable models - from data exploration and feature engineering through training, evaluation, deployment, and post-launch monitoring;
  • Develop new modeling patterns and analytical frameworks for forecasting (multivariate, hierarchical, causal-DAG, model-chaining) and optimization;
  • Build robust model validation, backtesting, and monitoring pipelines; identify and eliminate sources of leakage, bias, and silent failure;
  • Define and own model performance metrics (e.g., WAPE) tied to business outcomes;
  • Partner with Data Engineering and Software Development to productionize models and define I/O contracts, packaging, and model CI/CD;
  • Excellent communication to present findings, tradeoffs, and recommendations clearly to stakeholders and senior leadership.
View full posting on CareerOneStop → ID: d4f4fd89e4ba
Senior Product Data Scientist Manager, Android
Google · Kirkland, WA
Manager Master's
2026-05-27
Requirements
  • Bachelor's degree in Statistics, Mathematics, Data Science, Engineering, Physics, Economics, or a related quantitative field.
  • 13 years of work experience using analytics to solv.e product or business problems, performing statistical analysis, and coding (e.g., Python, R, SQL) (or 10 years work experience and a Master's degree)
  • 5 years of experience as a people manager within a technical leadership role.
Preferred
  • Master's degree in Statistics, Mathematics, Data Science, Engineering, Physics, Economics, or a related quantitative field.
  • 15 years of work experience using analytics to solve product or business problems, performing statistical analysis, and coding (e.g., Python, R, SQL).
  • 6 years of experience as a people manager within a technical leadership role.
Responsibilities
  • Android, Business, and Communications (ABC) is at the core of how people and businesses connect across the globe. Our mission is to build the world's most helpful, expressive, and secure communication experiences. With communication apps such as Google Messages and Dialer, we ship products that make a meaningful difference in billions of lives worldwide.
  • We define standard-setting "toothbrush journeys"-from fundamental calling reliability to high-resolution media sharing and expressive reactions. Beyond peer-to-peer connection, we are pioneering the next generation of conversational commerce, enabling businesses to deliver app-like experiences directly within the messaging interface. Whether adapting mobile features for a multi-device world on Wear OS or driving engagement with features like call screen, we focus on high-impact innovation that connects everyone, regardless of their device.
  • The Platforms and Devices team encompasses Google's various computing software platforms across environments (desktop, mobile, applications), as well as our first party devices and services that combine the best of Google AI, software, and hardware. Teams across this area research, design, and develop new technologies to make our user's interaction with computing faster and more seamless, building innovative experiences for our users around the world.
  • The US base salary range for this full-time position is $240,000-$334,000 + bonus + equity + benefits. Our salary ranges are determined by role, level, and location. Within the range, individual pay is determined by work location and additional factors, including job-related skills, experience, and relevant education or training. Your recruiter can share more about the specific salary range for your preferred location during the hiring process.
  • Please note that the compensation details listed in US role postings reflect the base salary only, and do not include bonus, equity, or benefits. Learn more aboutbenefits at Google (https://careers.google.com/benefits/) .
  • Perform analysis utilizing relevant tools (e.g., SQL, R, Python). Direct projects that combine analytical and organizational complexity towards clear, sound, and actionable decisions.
  • Own projects end-to-end, covering problem definition, metrics development, data extraction and manipulation, visualization, creation, implementation of analytical/statistical models, and presentation to stakeholders.
  • Address ambiguous or new problems by using the capabilities of existing systems and collaborate to turn broad problems into work for the team.
  • Oversee the integration of cross-functional and cross-organizational project/process timelines, drive improvements and recommendations, and define operational goals and objectives.
  • Lead a team of data scientists, oversee technical accuracy across the organization, provide essential technical oversight for ranking, personalization, and classification strategies to scale the business globally.
  • Information collected and processed as part of your Google Careers profile, and any job applications you choose to submit is subject to Google'sApplicant and Candidate Privacy Policy (./privacy-policy) .
View full posting on CareerOneStop → ID: c1b62ce0b414
Data Scientists - Finance
T-Mobile USA, Inc · Bellevue, WA
Mid-level Master's
2026-05-23
Requirements
  • (1) Applying statistical and mathematical methodologies including Linear Regression, Logistic Regression, Decision Tree, Cluster Analysis, and Hypothesis Testing to perform segmentation, prediction, forecast, and exploratory analysis;
  • (2) Extracting, integrating, and processing large-scale structured and unstructured datasets from multiple enterprise data warehouses and transactional databases using advanced SQL, Python and SAS. Performing data integrity checks to ensure completeness and accuracy under SOX compliance framework;
  • (3) Building and refining financial models to estimate the ASC 820 or IFRS 13 fair value of various assets and liabilities using US GAAP and IFRS compliant approaches by synthesizing data from internal systems, third-party market data, and historical financial performance;
  • (4) Performing fair value estimates of assets and liabilities using IFRS 13, IFRS 15, ASC460, ASC 606, ASC820, and ASC 805; and
  • (5) Interpreting and translating the results of statistical and mathematical methodologies including Linear Regression, Logistic Regression, Decision Tree, Cluster Analysis, and Hypothesis Testing and accounting fair value estimates using ASC 460, ASC 606, ASC 820, and ASC 805 prepared by the data scientist into actionable insights for accounting leadership.
Education
  • PRIMARY REQUIREMENTS: Master's degree in Measurement and Statistics, Applied Statistics, Financial Engineering, or related, and 1 year of relevant work experience.
  • ALTERNATIVE REQUIREMENTS: Bachelor's degree in Measurement and Statistics, Applied Statistics, Financial Engineering, or related, and 3 years of relevant work experience.
  • Location: Bellevue, WA
  • This position is eligible for the employee re
Responsibilities
  • Operate the model, coordinate with stake holders, and run a process to estimate the liability associated with the Jump Program.
  • Update the Jump liability program to increase efficiency for various stakeholders.
  • Provide adhoc analytics on various valuations.
  • Perform data analytics and statistical analysis to support forecast of device values.
  • Provide data analytics and statistical analysis to support the estimate of the Apple Forever Liability.
  • Work with various stakeholders to prepare a model to forecast credit losses on T-Mobile service contracts.
  • Understand key data architecture and changes to the company to provide insights to various stakeholders with respect to data and valuation estimates.
  • Telecommuting is permitted, but applicant must work from the worksite location at least 3-4 days per week.
  • Minimal amount of travel for training or conferences may be required periodically.
View full posting on CareerOneStop → ID: 558f8db1e0a6
Data Science Manager, PXT Central Science
Amazon · Seattle, WA
Manager Master's
2026-05-22
Requirements
  • 5+ years of building quantitative solutions as a scientist or science manager experience
  • 2+ years of scientists or machine learning engineers management experience
  • 5+ years of applying statistical models for large-scale application and building automated analytical systems experience
  • Master's degree in computer science, mathematics, statistics, machine learning or equivalent quantitative field
  • Knowledge of Python or R or other scripting language
Preferred
  • Experience in a least one area of Machine Learning (NLP, Regression, Classification, Clustering, or Anomaly Detection)
  • Experience with fairness in machine learning and artificial intelligence to detect and remove bias in ML/AI systems
Responsibilities
  • Leadership & Team Management: Independently manage and develop a diverse science team, creating an environment that enables consistent delivery and innovation; Build and maintain a high-performing team that can operate effectively and autonomously; Drive strategic growth opportunities for team members, providing paths to demonstrate higher-level scope, impact, and leadership; Establish clear performance metrics and audit mechanisms to track and communicate team progress; Foster a team culture focused on bringing research to production and delivering customer value
  • Technical & Scientific Direction: Partner with stakeholders and leadership to define and execute the scientific vision for your team; Lead the development of structural and predictive models, leveraging emerging technologies and novel features; Drive the implementation of data science workflows and simulation frameworks; Bridge the gap between science, technology, and business requirements; Leverage the broader Amazon scientific community to enhance team capabilities and knowledge sharing
  • Strategic Planning & Execution: Define and maintain team structure, strategic direction, and owned technologies; Establish processes that enable consistent delivery and quality of scientific artifacts; Drive reasonable schedules and adjust priorities to ensure optimal outcomes; Create and implement audit mechanisms to track team performance against goals; Remove roadblocks and optimize team productivity
  • Communication & Influence: Create well-written documents to effectively communicate with technical and non-technical audiences; Influence science and analytics practices across the organization; Build strong partnerships with stakeholders across different business units; Present complex scientific findings to senior leadership; Drive adoption of best practices and innovative solutions
View full posting on CareerOneStop → ID: 343cbeff7e60
Data Science Manager, PXT Central Science
Amazon · Bellevue, WA
Manager Master's
2026-05-22
Requirements
  • 5+ years of building quantitative solutions as a scientist or science manager experience
  • 2+ years of scientists or machine learning engineers management experience
  • 5+ years of applying statistical models for large-scale application and building automated analytical systems experience
  • Master's degree in computer science, mathematics, statistics, machine learning or equivalent quantitative field
  • Knowledge of Python or R or other scripting language
Preferred
  • Experience in a least one area of Machine Learning (NLP, Regression, Classification, Clustering, or Anomaly Detection)
  • Experience with fairness in machine learning and artificial intelligence to detect and remove bias in ML/AI systems
Responsibilities
  • Leadership & Team Management: Independently manage and develop a diverse science team, creating an environment that enables consistent delivery and innovation; Build and maintain a high-performing team that can operate effectively and autonomously; Drive strategic growth opportunities for team members, providing paths to demonstrate higher-level scope, impact, and leadership; Establish clear performance metrics and audit mechanisms to track and communicate team progress; Foster a team culture focused on bringing research to production and delivering customer value
  • Technical & Scientific Direction: Partner with stakeholders and leadership to define and execute the scientific vision for your team; Lead the development of structural and predictive models, leveraging emerging technologies and novel features; Drive the implementation of data science workflows and simulation frameworks; Bridge the gap between science, technology, and business requirements; Leverage the broader Amazon scientific community to enhance team capabilities and knowledge sharing
  • Strategic Planning & Execution: Define and maintain team structure, strategic direction, and owned technologies; Establish processes that enable consistent delivery and quality of scientific artifacts; Drive reasonable schedules and adjust priorities to ensure optimal outcomes; Create and implement audit mechanisms to track team performance against goals; Remove roadblocks and optimize team productivity
  • Communication & Influence: Create well-written documents to effectively communicate with technical and non-technical audiences; Influence science and analytics practices across the organization; Build strong partnerships with stakeholders across different business units; Present complex scientific findings to senior leadership; Drive adoption of best practices and innovative solutions
View full posting on CareerOneStop → ID: c4a3c0ed4ac4
Machine Learning Engineer
Zoom · Seattle, WA
Mid-level Master's
2026-05-22
Responsibilities
  • Design, implement, and optimize GenAI algorithms, techniques and solutions to address complex
  • business challenges.
  • Collaborate with cross-functional teams to integrate research findings into scalable engineering solutions that align with business objectives.
  • Participate in code reviews, design discussions, and technical presentations to ensure the quality and reliability of our engineering solutions.
  • Identify opportunities for improvement in existing systems and proposing innovative solutions to enhance performance, scalability, and reliability.
  • Stay up to date with the newest developments in GenAI research and engineering to continuously improve our technical capabilities.
  • What we're looking for:
  • Requires a Bachelor's degree in Computer Science, Computer Engineering, a related field, or a foreign degree equivalent. Must have 3 years of experience in job offered or related occupation. Must have 3 years of experience in the following skills:
  • Utilizing one or more programming languages such as Python, C, C++, or CUDA in building scalable software systems;
  • Deep learning frameworks including PyTorch and TensorFlow;
  • Presenting academic or personal AI projects;
  • Collaborating with cross-functional teams to present technical concepts to both technical and nontechnical audiences;
  • Agentic AI including LLM driven AI agents, agentic RAG;
  • Building scalable, maintainable, and production-ready machine learning systems; and
  • Analyzing data and troubleshooting issues related to deployed AI systems.
  • Telecommuting work arrangement permitted one day per week. Four days in office required. Position does not require domestic or international travel.
  • In Lieu of a Bachelor's degree and 3 years of experience the company will accept the following: Must have Master's degree in Computer Science, Computer Engineering, a related field, or a foreign degree equivalent. Must have 1 years of experience in job offered or related occupation. Must have 1 years of experience in the following skills:
View full posting on CareerOneStop → ID: e5af510de9ba
Senior Data Scientist - Fleet Analytics
The Hertz Corporation · Olympia, WA
Senior Master's
2026-05-21
Requirements
  • 3-5 years hands-on experience in a data scientist role
  • 3+ years of data querying languages (e.g. SQL) and scripting languages (e.g. Python)
  • 3+ years of end-to-end machine learning model development experience (e.g. problem statement definition, exploratory data analysis, feature engineering, model development / tuning, and deployment)
  • Demonstrated experience using machine learning to drive a business impact
  • Experience in a ML or data scientist role with car rental or technology company.
  • Bachelor or Masters degree in Computer Science, or other quantitative discipline such as statistics, mathematics, physics or engineering
  • *What You'll Get:
  • Up to 40% off any standard Hertz Rental??
  • Medical, Dental & Vision plan options
  • Retirement programs, including 401(k) employer matching
  • Paid Parental Leave & Adoption Assistance
  • Employee Assistance Program for employees & family
  • Educational Reimbursement & Discounts
  • Voluntary Insurance Programs - Pet, Legal/Identity Theft, Critical Illness
  • Perks & Discounts -Theme Park Tickets, Gym Discounts & more
  • The Hertz Corporation operates the Hertz, Dollar Car Rental, Thrifty Car Rental brands in approximately 9,700 corporate and franchisee locations throughout North America, Europe, The Caribbean, Latin America, Africa, the Middle East, Asia, Australia and New Zealand. The Hertz Corporation is one of the largest worldwide airport general use vehicle rental companies, and the Hertz brand is one of the most recognized in the world.
Responsibilities
  • At Hertz, we are at the forefront of innovation, leveraging cutting-edge technologies to build the best damage management technologies in the transportation industry. We want the brightest AI & ML minds to join our Damage Science Team to help us develop and/or maintain capabilities. Examples of projects the team work on include the below:L
  • Rationalize Repair Estimates and Invoices with Large Language Models (LLMs): Implement sophisticated LLMs to make intelligent repair routing decisions, ensuring repairs are conducted efficiently and cost-effectively.
  • Forecast Repair Needs: Develop models to predict future repair & maintenance needs based on historical data and trends.
  • Optimize Decision Making: Create models to determine if we should keep/sell/salvage a vehicle.
  • Demand Planning: Forecast customer demand at a given location at a given time.
  • *What You Will Do:
  • Formulate the strategic and tactical steps to carry out the model development lifecycle end-to-end (i.e. problem statement definition, exploratory data analysis, feature engineering, model development / tuning, and model implementation).
  • Build and maintain descriptive, predictive, and prescriptive models to measure the performance of the new products and services
  • Define and implement best practices to generate accurate analytics, reports, visualizations, and dashboards to explain results simply and succinctly to technical, non-technical, and senior management
  • Build partnerships and work cross-functionally to identify use cases and opportunities to enhance operational efficiency and drive business value through positive impact on OKRs.
  • Work with an owner mentality to drive business impact even if that means supporting pipeline creation or decision support analytics.
View full posting on CareerOneStop → ID: 286df7c97cda
Senior Data Scientist - Fleet Analytics
The Hertz Corporation · Boise, ID
Senior Master's
2026-05-21
Requirements
  • 3-5 years hands-on experience in a data scientist role
  • 3+ years of data querying languages (e.g. SQL) and scripting languages (e.g. Python)
  • 3+ years of end-to-end machine learning model development experience (e.g. problem statement definition, exploratory data analysis, feature engineering, model development / tuning, and deployment)
  • Demonstrated experience using machine learning to drive a business impact
  • Experience in a ML or data scientist role with car rental or technology company.
  • Bachelor or Masters degree in Computer Science, or other quantitative discipline such as statistics, mathematics, physics or engineering
  • *What You'll Get:
  • Up to 40% off any standard Hertz Rental??
  • Medical, Dental & Vision plan options
  • Retirement programs, including 401(k) employer matching
  • Paid Parental Leave & Adoption Assistance
  • Employee Assistance Program for employees & family
  • Educational Reimbursement & Discounts
  • Voluntary Insurance Programs - Pet, Legal/Identity Theft, Critical Illness
  • Perks & Discounts -Theme Park Tickets, Gym Discounts & more
  • The Hertz Corporation operates the Hertz, Dollar Car Rental, Thrifty Car Rental brands in approximately 9,700 corporate and franchisee locations throughout North America, Europe, The Caribbean, Latin America, Africa, the Middle East, Asia, Australia and New Zealand. The Hertz Corporation is one of the largest worldwide airport general use vehicle rental companies, and the Hertz brand is one of the most recognized in the world.
Responsibilities
  • At Hertz, we are at the forefront of innovation, leveraging cutting-edge technologies to build the best damage management technologies in the transportation industry. We want the brightest AI & ML minds to join our Damage Science Team to help us develop and/or maintain capabilities. Examples of projects the team work on include the below:L
  • Rationalize Repair Estimates and Invoices with Large Language Models (LLMs): Implement sophisticated LLMs to make intelligent repair routing decisions, ensuring repairs are conducted efficiently and cost-effectively.
  • Forecast Repair Needs: Develop models to predict future repair & maintenance needs based on historical data and trends.
  • Optimize Decision Making: Create models to determine if we should keep/sell/salvage a vehicle.
  • Demand Planning: Forecast customer demand at a given location at a given time.
  • *What You Will Do:
  • Formulate the strategic and tactical steps to carry out the model development lifecycle end-to-end (i.e. problem statement definition, exploratory data analysis, feature engineering, model development / tuning, and model implementation).
  • Build and maintain descriptive, predictive, and prescriptive models to measure the performance of the new products and services
  • Define and implement best practices to generate accurate analytics, reports, visualizations, and dashboards to explain results simply and succinctly to technical, non-technical, and senior management
  • Build partnerships and work cross-functionally to identify use cases and opportunities to enhance operational efficiency and drive business value through positive impact on OKRs.
  • Work with an owner mentality to drive business impact even if that means supporting pipeline creation or decision support analytics.
View full posting on CareerOneStop → ID: 6d1d2cdf3f61
Senior Data Scientist - Fleet Analytics
The Hertz Corporation · Salem, OR
Senior Master's
2026-05-21
Requirements
  • 3-5 years hands-on experience in a data scientist role
  • 3+ years of data querying languages (e.g. SQL) and scripting languages (e.g. Python)
  • 3+ years of end-to-end machine learning model development experience (e.g. problem statement definition, exploratory data analysis, feature engineering, model development / tuning, and deployment)
  • Demonstrated experience using machine learning to drive a business impact
  • Experience in a ML or data scientist role with car rental or technology company.
  • Bachelor or Masters degree in Computer Science, or other quantitative discipline such as statistics, mathematics, physics or engineering
  • *What You'll Get:
  • Up to 40% off any standard Hertz Rental??
  • Medical, Dental & Vision plan options
  • Retirement programs, including 401(k) employer matching
  • Paid Parental Leave & Adoption Assistance
  • Employee Assistance Program for employees & family
  • Educational Reimbursement & Discounts
  • Voluntary Insurance Programs - Pet, Legal/Identity Theft, Critical Illness
  • Perks & Discounts -Theme Park Tickets, Gym Discounts & more
  • The Hertz Corporation operates the Hertz, Dollar Car Rental, Thrifty Car Rental brands in approximately 9,700 corporate and franchisee locations throughout North America, Europe, The Caribbean, Latin America, Africa, the Middle East, Asia, Australia and New Zealand. The Hertz Corporation is one of the largest worldwide airport general use vehicle rental companies, and the Hertz brand is one of the most recognized in the world.
Responsibilities
  • At Hertz, we are at the forefront of innovation, leveraging cutting-edge technologies to build the best damage management technologies in the transportation industry. We want the brightest AI & ML minds to join our Damage Science Team to help us develop and/or maintain capabilities. Examples of projects the team work on include the below:L
  • Rationalize Repair Estimates and Invoices with Large Language Models (LLMs): Implement sophisticated LLMs to make intelligent repair routing decisions, ensuring repairs are conducted efficiently and cost-effectively.
  • Forecast Repair Needs: Develop models to predict future repair & maintenance needs based on historical data and trends.
  • Optimize Decision Making: Create models to determine if we should keep/sell/salvage a vehicle.
  • Demand Planning: Forecast customer demand at a given location at a given time.
  • *What You Will Do:
  • Formulate the strategic and tactical steps to carry out the model development lifecycle end-to-end (i.e. problem statement definition, exploratory data analysis, feature engineering, model development / tuning, and model implementation).
  • Build and maintain descriptive, predictive, and prescriptive models to measure the performance of the new products and services
  • Define and implement best practices to generate accurate analytics, reports, visualizations, and dashboards to explain results simply and succinctly to technical, non-technical, and senior management
  • Build partnerships and work cross-functionally to identify use cases and opportunities to enhance operational efficiency and drive business value through positive impact on OKRs.
  • Work with an owner mentality to drive business impact even if that means supporting pipeline creation or decision support analytics.
View full posting on CareerOneStop → ID: 19e6bdef9dfe
Finance Manager, Advertising Finance - Measurement, Ad Tech, and Data Science (MADS)
Amazon · Seattle, WA
Manager Master's
2026-05-20
Requirements
  • Bachelor's degree in Finance, Accounting, Business, Economics or a highly analytical field (e.g., Engineering, Math, and Computer Science)
  • 5+ years of finance or a related analytical field experience
  • Experience coordinating between technical teams, peers and business stakeholders
  • 5+ years of experience creating financial models and strategic analyses that support business decisions
Preferred
  • Experience in TM1, Data Warehouse and SQL
  • Experience with AI/ML technologies
  • Experience leading financial technology automation and process improvement initiatives with tech and non-tech teams
  • Advertising or Media experience is a plus
Responsibilities
  • Business Partnering & Performance Management
  • Serve as the finance partner for Performance Measurement and Infrastructure leadership
  • Advise engineering and product leaders on risks, opportunities, and trade-offs impacting quarterly and annual goals
  • Run weekly business reviews, define and report KPIs, and communicate financials to senior MADS leadership
  • Support monthly business reviews with insights, variance analysis, and recommendations
  • Strategic Analysis & Cost Management
  • Manage hardware cost analysis for Infrastructure, partnering with engineering on capacity planning and cost efficiency
  • Provide financial modeling and strategic analysis for PRFAQs, product roadmap decisions, and investment trade-offs
  • Deliver analyses that translate complex technical problems into actionable insights for senior leadership
  • Partner with BIE and analytics teams to build scalable dashboards and automated reporting
  • Cross-Functional Collaboration & Operational Excellence
  • Partner with product, engineering, data science, and sales teams to align strategy with business priorities
  • Collaborate across Advertising Finance to ensure consistency in planning and reporting
  • Leverage AI tools daily to raise the speed and quality of finance work, and build AI-powered solutions for the team
  • Drive process improvements that simplify and scale finance mechanisms, insisting on the highest standards in data accuracy and rigo
View full posting on CareerOneStop → ID: 0c166170a6d9
Principal Product Manager, Data Science
Norstella · Olympia, WA
Manager Master's
2026-05-20
Requirements
  • 6+ years of experience applying AI / ML to business applications and delivering data driven solutions.
  • Proven track record of innovating on behalf of the customer in close collaboration with business teams and delivering revenue generating products into production.
  • Graduate degree in Computer Science, Engineering, Statistics or a related quantitative discipline, or equivalent work experience.
  • Substantial depth and breadth in NLP, Deep Learning, Generative AI and other state of the art AI / ML techniques.
  • Excellent knowledge of high-level programming languages (Python, Java, or C++) and core data science libraries including Pandas, NumPy and other similar libraries.
  • Experience with delivering large-scale distributed systems in an agile environment and the ability to build quick prototypes.
  • Experience leading a portfolio of complex data science projects and mentoring junior team members.
  • Excellent problem solving and communication skills.
Preferred
  • Knowledge of the healthcare domain and experience with applying AI to healthcare data.
  • Experience with AWS especially in relation to ML workflows with SageMaker, serverless compute and storage such as S3 and Snowflake.
  • Experience with LLMs, prompt engineering, retrieval augmented generation, model fine tuning and knowledge graphs.
Responsibilities
  • In this role as a Principal Product Manager, Data Science, you will:
  • Collaborate with product leadership to identity, elaborate and prioritize projects.
  • Partner with business-product managers to explore new opportunities to build customer facing capabilities with AI and build and maintain the data science project pipeline.
  • Help define requirements and success metrics for identified projects and collaborate with data scientists and engineers to deliver on the commitments.
  • Lead marketing activities for the data science team, facilitate ideation sessions to help the entire product organization innovate, and introduce processes that promote transparent prioritization, data-driven decision making, and reuse of our platforms and capabilities across the company.
  • Stay up-to-date, constantly learning about advances in the field, and deliver periodic presentations to internal teams on these developments.
  • Serve as the company-wide expert in one or more complex technical areas and its business applications (e.g., entity mastering, knowledge graphs, search optimization, RAG).
  • All other duties, as assigned.
View full posting on CareerOneStop → ID: 352068afaa9f
Data Scientist II
Chewy Inc. · Bellevue, WA
Mid-level Master's
2026-05-20
Requirements
  • Ability to work with large datasets using distributed computing tools;
  • Amazon Web Services tools such as Redshift, Snowflake, Google Big Query, SageMaker or other similar platforms;
  • Object-oriented programming with Python; and
  • Data visualization tools and packages (Tableau or similar).
View full posting on CareerOneStop → ID: 0ef76487d159
Principal Product Manager, Data Science
Norstella · Boise, ID
Manager Master's
2026-05-20
Requirements
  • 6+ years of experience applying AI / ML to business applications and delivering data driven solutions.
  • Proven track record of innovating on behalf of the customer in close collaboration with business teams and delivering revenue generating products into production.
  • Graduate degree in Computer Science, Engineering, Statistics or a related quantitative discipline, or equivalent work experience.
  • Substantial depth and breadth in NLP, Deep Learning, Generative AI and other state of the art AI / ML techniques.
  • Excellent knowledge of high-level programming languages (Python, Java, or C++) and core data science libraries including Pandas, NumPy and other similar libraries.
  • Experience with delivering large-scale distributed systems in an agile environment and the ability to build quick prototypes.
  • Experience leading a portfolio of complex data science projects and mentoring junior team members.
  • Excellent problem solving and communication skills.
Preferred
  • Knowledge of the healthcare domain and experience with applying AI to healthcare data.
  • Experience with AWS especially in relation to ML workflows with SageMaker, serverless compute and storage such as S3 and Snowflake.
  • Experience with LLMs, prompt engineering, retrieval augmented generation, model fine tuning and knowledge graphs.
Responsibilities
  • In this role as a Principal Product Manager, Data Science, you will:
  • Collaborate with product leadership to identity, elaborate and prioritize projects.
  • Partner with business-product managers to explore new opportunities to build customer facing capabilities with AI and build and maintain the data science project pipeline.
  • Help define requirements and success metrics for identified projects and collaborate with data scientists and engineers to deliver on the commitments.
  • Lead marketing activities for the data science team, facilitate ideation sessions to help the entire product organization innovate, and introduce processes that promote transparent prioritization, data-driven decision making, and reuse of our platforms and capabilities across the company.
  • Stay up-to-date, constantly learning about advances in the field, and deliver periodic presentations to internal teams on these developments.
  • Serve as the company-wide expert in one or more complex technical areas and its business applications (e.g., entity mastering, knowledge graphs, search optimization, RAG).
  • All other duties, as assigned.
View full posting on CareerOneStop → ID: 0925bd9bfd98
Principal Product Manager, Data Science
Norstella · Salem, OR
Manager Master's
2026-05-20
Requirements
  • 6+ years of experience applying AI / ML to business applications and delivering data driven solutions.
  • Proven track record of innovating on behalf of the customer in close collaboration with business teams and delivering revenue generating products into production.
  • Graduate degree in Computer Science, Engineering, Statistics or a related quantitative discipline, or equivalent work experience.
  • Substantial depth and breadth in NLP, Deep Learning, Generative AI and other state of the art AI / ML techniques.
  • Excellent knowledge of high-level programming languages (Python, Java, or C++) and core data science libraries including Pandas, NumPy and other similar libraries.
  • Experience with delivering large-scale distributed systems in an agile environment and the ability to build quick prototypes.
  • Experience leading a portfolio of complex data science projects and mentoring junior team members.
  • Excellent problem solving and communication skills.
Preferred
  • Knowledge of the healthcare domain and experience with applying AI to healthcare data.
  • Experience with AWS especially in relation to ML workflows with SageMaker, serverless compute and storage such as S3 and Snowflake.
  • Experience with LLMs, prompt engineering, retrieval augmented generation, model fine tuning and knowledge graphs.
Responsibilities
  • In this role as a Principal Product Manager, Data Science, you will:
  • Collaborate with product leadership to identity, elaborate and prioritize projects.
  • Partner with business-product managers to explore new opportunities to build customer facing capabilities with AI and build and maintain the data science project pipeline.
  • Help define requirements and success metrics for identified projects and collaborate with data scientists and engineers to deliver on the commitments.
  • Lead marketing activities for the data science team, facilitate ideation sessions to help the entire product organization innovate, and introduce processes that promote transparent prioritization, data-driven decision making, and reuse of our platforms and capabilities across the company.
  • Stay up-to-date, constantly learning about advances in the field, and deliver periodic presentations to internal teams on these developments.
  • Serve as the company-wide expert in one or more complex technical areas and its business applications (e.g., entity mastering, knowledge graphs, search optimization, RAG).
  • All other duties, as assigned.
View full posting on CareerOneStop → ID: 04cc7306bca0
Machine Learning Engineer, Apple Services Engineering
Apple · Seattle, WA
Mid-level Master's
2026-05-19
Requirements
  • Bachelor's degree in Computer Science, Software Engineering, Mathematics, or a related technical field.
  • 7+ years of relevant work experience.
  • Strong software engineering fundamentals and technical competence in production-quality software development.
  • Real-world experience with building, scaling, and deploying recommendation systems or large-scale ML models.
  • Proven grasp of the open-source Python AI/ML tech stack, including PyTorch, scikit-learn, and numpy-scipy-pandas.
  • Solid understanding of machine learning algorithms, design patterns, and tools, including deep learning and generative AI.
  • Proficiency with big data technologies, data processing pipelines, and distributed computing (e.g., Spark, Hadoop, Kafka).
  • Experience with ML infrastructure, model optimization, and serving models at scale with low latency.
  • Strong written & oral communication skills, with a collaborative mindset.
Preferred
  • Master's degree in Computer Science, Software Engineering, Mathematics, or a related field; OR equivalent practical industry experience.
  • Industry experience specifically focused on MLOps, recommendation systems, or search ranking infrastructure.
Responsibilities
  • Wonder how Apple's Media Products show relevant search results and recommendations across Apple's media offerings - including App Store, Apple TV, Apple Music, Apple Podcasts, and Apple Books? Come join us! Design, build, and deploy machine learning pipelines that personalize the App Store for billions of users worldwide! Prototype, scale, and optimize algorithm improvements. Build robust, large-scale personalized recommender systems for Apps, Games, Videos, Podcasts and Fitness. See your work touch the lives of billions of Apple users worldwide.
  • The Apple Services Engineering team is one of the most exciting examples of Apple's long-held passion for combining art and technology. We are the people who power the App Store, Apple TV, Apple Music, Apple Podcasts, and Apple Fitness+. And we do it on a massive scale, meeting Apple's high expectations with high performance, to deliver a huge variety of entertainment in over 35 languages to more than 150 countries.
  • Our scientists and engineers build secure, end-to-end solutions powered by machine learning. Thanks to Apple's unique integration of hardware, software, and services, designers, scientists and engineers here partner to get behind a single unified vision. That vision always includes a deep commitment to strengthening Apple's privacy policy, one of Apple's core values. Although services are a bigger part of Apple's business than ever before, these teams remain small, flexible, and multi-functional, offering greater exposure to the array of opportunities here.
  • We are looking for an exceptional Machine Learning Engineer to help us build and scale personalization systems using the latest advances in machine learning. With your engineering expertise, we want to develop robust, high-performance solutions to power personalized experiences across the App Store that enrich the lives of our customers. You will have the incredible opportunity to partner with researchers to see cutting-edge AI models deployed reliably at Apple's truly incredible global scale.
View full posting on CareerOneStop → ID: 10a0a4edb19a
Sr Engineer, Machine Learning Engineering
T-Mobile USA, Inc · Bellevue, WA
Senior Master's
2026-05-17
Education
  • Bachelor's Degree Computer Science, Data Science, Statistics, Informatics, Information Systems, Machine Learning, or another quantitative field (Required)
  • Master's/Advanced Degree Computer Science, Data Science, Statistics, Informatics, Information Systems, Machine Learning, or another quantitative field (Preferred)
  • 1+ year of experience in designing, developing, and deploying large language models (LLMs) and generative AI systems in production environments (Required)
  • 5+ years of experience building and maintaining end-to-end ML pipelines, including data ingestion, training, deployment, monitoring, and optimization (Required)
  • 3+ years of experience applying MLOps practices and leveraging cloud platforms (AWS, GCP, or Azure) for scalable AI solutions (Required)
  • Experience implementing fine-tuning, evaluation, and benchmarking techniques for LLMs and generative AI applications (Preferred)
  • 5+ years of experience collaborating with cross-functional teams (engineering, data scienc
Responsibilities
  • The Senior Engineer, Machine Learning plays a pivotal role in advancing AI capabilities, focusing on the design, development, and deployment of large language models (LLMs) and generative AI solutions. This position is essential for building scalable, production-grade AI systems that enable automation, personalization, and intelligent decision-making across the enterprise. The role emphasizes the creation of innovative GenAI applications that deliver real-world business impact while maintaining high standards of performance, reliability, and responsible AI practices. Collaborating with cross-functional technical teams, they ensure the seamless integration of LLM-powered solutions into products and workflows, reinforcing the organization's leadership in applying advanced AI technologies.
  • Build and manage the complete machine learning and generative AI lifecycle, including research, design, experimentation, development, deployment, monitoring, and maintenance.
  • Design, develop, and deploy LLM-based and generative AI models to power scalable and intelligent enterprise applications.
  • Architect, optimize, and maintain retrieval-augmented generation (RAG), prompt orchestration, and contextual reasoning pipelines to support diverse AI use cases.
  • Implement scalable MLOps pipelines for model deployment, performance monitoring, and continuous improvement.
  • Conduct fine-tuning, alignment, and evaluation of LLMs and multimodal models to ensure reliability, efficiency, and fairness.
  • Collaborate with data science, engineering, and product teams to translate business needs into generative AI-driven solutions.
  • Perform benchmarking, evaluation, and optimization of generative models to improve accuracy, latency, and cost efficiency.
  • Research and apply emerging techniques in transformer architectures, multimodal learning, and generative modeling to drive innovation and enhance enterprise capabilities.
  • Ensure secure, ethical, and responsible AI deployment, embedding fairness, transparency, and compliance throughout the model lifecycle.
  • Mentor and guide team members on generative AI frameworks, best practices, and experimentation methodologies.
  • Participate in other duties or projects as assigned by business management as needed.
View full posting on CareerOneStop → ID: 6fbcb19eb395
Sr Data Scientist- Consumer Analytics
T-Mobile USA, Inc · Bellevue, WA
Senior Master's
2026-05-16
Education
  • Bachelor's Degree plus 5 years of related work experience OR Advanced degree with 3 years of related experience (Required)
  • Acceptable areas of study include Quantitative Discipline (math, statistics, economics, computer science, physics, engineering, etc.) (Required)
  • 4-7 years Industry experience in predictive modeling, data science, and analysis in an ML engineer or data scientist role building and deploying ML models or hands on experience developing deep learning models (Required)
  • 4-7 years Experience with data scripting languages (e.g., SQL, Python, R) (Required)
  • 2-4 years Experience with big data architecture and pipeline, Hadoop, Hive, Spark, Kafka, etc. (Required)
  • 4-7 years Experience articulating and translating business questions and using statistical techniques to arrive at an answer using available data (Required)
  • 4-7 years Experience in data visualization (Required)
  • 4-7 years Experience working with relational database using SQL (Required)
  • 2-4 years Experience in the telecom industry (Preferred)
  • *Knowledge, Skills and Abilities:
  • Mathematics Calculus, linear algebra, statistics, and probability (Required)
  • Programming Expertise in Python and SQL (Required)
  • Machine Learning: Expertise applying machine learning concepts and techniques related to supervised and unsupervised learning (Required)
  • At least 18 years of age
  • Legally authorized to work in the United States
  • *Travel:Travel Required (Yes/No): NoDOT Regulated:DOT Regulated Position (Yes/No): NoSafety Sensitive Position (Yes/No): No
  • Base Pay Range: $106,000 - $191,100
Responsibilities
  • This role leads the application of machine learning techniques and statistical methods to address complex business challenges effectively. It involves collaborating with diverse technical and non-technical stakeholders to deliver data-driven solutions. The role requires expertise across the entire machine learning lifecycle, including problem framing, data collection, model development, deployment, and performance evaluation. Success is measured by the ability to create actionable insights and deploy models that drive informed decision-making and business value. The work impacts organizational outcomes by transforming data into strategic assets that support business objectives and customer needs.
  • Extract and model large, complex data sets using machine learning, mathematics, statistics, and programming to generate predictive insights
  • Deliver timely, high-quality analysis and actionable recommendations that support intelligent business decision-making
  • Provide senior-level guidance and mentorship by reviewing projects, models, and code to support team development
  • Collaborate with engineering teams to implement and enhance machine learning pipelines and production-ready models
  • Communicate key information and insights to business leaders through verbal, written, and data visualization methods
  • Also responsible for other duties/projects as assigned by business management as needed
View full posting on CareerOneStop → ID: 10389d929b61
Staff Data Scientist, Product
Google · Kirkland, WA
Senior Master's
2026-05-16
Requirements
  • Bachelor's degree in Statistics, Mathematics, Data Science, Engineering, Physics, Economics, or a related quantitative field.
  • 10 years of work experience using analytics to solve product or business problems, performing statistical analysis, and coding (e.g., Python, R, SQL) (or 8 years work experience plus a Master's degree).
Preferred
  • Master's degree in Statistics, Mathematics, Data Science, Engineering, Physics, Economics, or a related quantitative field.
  • 12 years of work experience using analytics to solve product or business problems, performing statistical analysis, and coding (e.g., Python, R, SQL).
Responsibilities
  • Help serve Google's worldwide user base of more than a billion people. Data Scientists provide quantitative support, market understanding and a strategic perspective to our partners throughout the organization. As a data-loving member of the team, you serve as an analytics expert for your partners, using numbers to help them make better decisions. You will weave stories with meaningful insight from data. You'll make critical recommendations for your fellow Googlers in Engineering and Product Management. You relish tallying up the numbers one minute and communicating your findings to a team leader the next.
  • Google is an engineering company at heart. We hire people with a broad set of technical skills who are ready to take on some of technology's greatest challenges and make an impact on users around the world. At Google, engineers not only revolutionize search, they routinely work on scalability and storage solutions, large-scale applications and entirely new platforms for developers around the world. From Google Ads to Chrome, Android to YouTube, social to local, Google engineers are changing the world one technological achievement after another.
  • The US base salary range for this full-time position is $192,000-$278,000 + bonus + equity + benefits. Our salary ranges are determined by role, level, and location. Within the range, individual pay is determined by work location and additional factors, including job-related skills, experience, and relevant education or training. Your recruiter can share more about the specific salary range for your preferred location during the hiring process.
  • Please note that the compensation details listed in US role postings reflect the base salary only, and do not include bonus, equity, or benefits. Learn more aboutbenefits at Google (https://careers.google.com/benefits/) .
  • Perform analysis utilizing relevant tools (e.g., SQL, R, Python). Provide analytical thought leadership through proactive and strategic contributions (e.g., suggests new analyses, infrastructure or experiments to drive improvements in the business).
  • Own outcomes for projects by covering problem definition, metrics development, data extraction and manipulation, visualization, creation, and implementation of analytical/statistical models, and presentation to stakeholders.
  • Develop solutions, lead, and manage problems that may be ambiguous and lacking clear precedent by framing problems, generating hypotheses, and making recommendations from a perspective that combines both, analytical and product-specific expertise.
  • Oversee the integration of cross-functional and cross-organizational project/process timelines, develop process improvements and recommendations, and help define operational goals and objectives.
  • Directly or indirectly oversee the contributions of others and develop colleagues' capabilities in the area of specialization.
  • Information collected and processed as part of your Google Careers profile, and any job applications you choose to submit is subject to Google'sApplicant and Candidate Privacy Policy (./privacy-policy) .
View full posting on CareerOneStop → ID: 87b6f7a2eaef
Sr. Staff AI/ML Engineer
WEX INC · Seattle, WA
Senior Master's
2026-05-15
Requirements
  • 12+ years of professional software or ML engineering experience, with a track record of deploying production-grade AI systems.
  • Proficiency in Python and key machine learning frameworks (PyTorch, TensorFlow, or similar).
  • Strong working knowledge of core libraries (NumPy, Pandas, scikit-learn) and LLM development frameworks (LangChain, ADK, or similar).
  • Experience with cloud platforms (AWS preferred; Azure or GCP also valuable) and Infrastructure-as-Code tools like Terraform.
  • Deep familiarity with CI/CD pipelines and DevOps practices using GitHub Actions or similar platforms.
  • Demonstrated ability to operate in agile, collaborative, high-trust teams.
  • Bachelor's degree in Computer Science, Engineering, or a related discipline (Master's preferred).
  • Bonus: Experience in financial systems, data compliance, or building multi-tenant Agentic AI applications.
  • You'll work within
Responsibilities
  • Location:This is a remote position; however, the candidate must reside within 30 miles of one of the following locations: Portland, ME; Boston, MA; Chicago, IL; Dallas, TX; San Francisco Bay Area, CA; and Seattle/WA.
  • AI Platform Engineering, WEX Inc.
  • Lead the design, implementation, and production deployment of machine learning and AI-driven systems-including LLM-based and agentic applications.
  • Partner with AI platform and product engineering teams to integrate advanced AI capabilities into WEX's enterprise systems.
  • Design and maintain ML pipelines, from data ingestion to model deployment, ensuring scalability, observability, and reusability across teams.
  • Build and expose AI functionality via RESTful APIs and micro-services architectures.
  • Champion engineering best practices: CI/CD, infrastructure-as-code, testing automation, and continuous improvement.
  • Contribute to architectural decisions with a focus on security, compliance, and performance-especially in regulated industries such as payments and healthcare.
  • Collaborate cross-functionally with data scientists, ML engineers, and business stakeholders to align technical solutions with strategic goals.
View full posting on CareerOneStop → ID: 35ab92981071
Data Scientist - Research Informatics
Seattle Children's · Seattle, WA
Mid-level Master's
2026-05-14
Education
  • Bachelor's degree or higher in a STEM or relevant analytical field that demonstrates analytical and technical competency and 2+ years as a Data Analyst using data science tools and methods OR a Master's in a STEM or relevant analytical field that demonstrates analytical and technical competency with evidence of work or applied research experience using data science tools and methods.
  • Experience with statistics as well as machine learning/data mining/etc.
  • Experience developing and using statistical models and algorithms.
  • Intermediate or higher experience in least one major data science language (e.g., R, Python).
  • Experience in use of data visualization tools and methods.
  • Experience working with source control tools and version management.
  • Experience in data extraction using at least one data manipulation language/package(e.g., SQL, R-dplyr, SAS DATA step, Python-pandas).
  • Experience as a member of a delivery team supporting integrated data science products and solutions for a wide range of customer groups.
  • *Required Credentials
View full posting on CareerOneStop → ID: 2eeab0445572
AI & GenAI Data Scientist - EUR- Director
PwC · Seattle, WA
Director Master's
2026-05-10
Requirements
  • Bachelor's Degree
  • 10 years of experience
  • What Sets You Apart
  • Master's Degree preferred
  • Managing AI and GenAI solution development teams
  • Experience in Energy and Utilities Industry
  • Documenting and analyzing business processes for AI
  • Designing AI/GenAI architectures for plugin-based solutions
  • Managing global data and analytics team operations
  • Leading development of proof of concepts and pilots
  • Facilitating executive level presentations on GenAI solutions
  • Managing GenAI application development teams
  • Experience with Python, LLM frameworks, and cloud platforms
  • The salary range for this position is: $155,000 - $410,000. Actual compensation within the range will be dependent upon the individual's skills, experience, qualifications and location, and applicable employment laws. All hired individuals are eligible for an annual discretionary bonus. PwC offers a wide range of benefits, including medical, dental, vision, 401k, holiday pay, vacation, personal and family sick leave, and more. To view our benefits at a glance, please visit the following link: https://pwc.to/benefits-at-a-glance
Responsibilities
  • Guide the strategic direction for AI and GenAI solution development
  • Develop and refine AI/GenAI architectures for client needs
  • Foster collaboration across data and analytics teams
  • Align with client objectives and industry standards
  • Promote technological advancements in data-driven solutions
View full posting on CareerOneStop → ID: a637e47c1997
AI & GenAI Data Scientist - EUR- Director
PwC · Portland, OR
Director Master's
2026-05-10
Requirements
  • Bachelor's Degree
  • 10 years of experience
  • What Sets You Apart
  • Master's Degree preferred
  • Managing AI and GenAI solution development teams
  • Experience in Energy and Utilities Industry
  • Documenting and analyzing business processes for AI
  • Designing AI/GenAI architectures for plugin-based solutions
  • Managing global data and analytics team operations
  • Leading development of proof of concepts and pilots
  • Facilitating executive level presentations on GenAI solutions
  • Managing GenAI application development teams
  • Experience with Python, LLM frameworks, and cloud platforms
  • The salary range for this position is: $155,000 - $410,000. Actual compensation within the range will be dependent upon the individual's skills, experience, qualifications and location, and applicable employment laws. All hired individuals are eligible for an annual discretionary bonus. PwC offers a wide range of benefits, including medical, dental, vision, 401k, holiday pay, vacation, personal and family sick leave, and more. To view our benefits at a glance, please visit the following link: https://pwc.to/benefits-at-a-glance
Responsibilities
  • Guide the strategic direction for AI and GenAI solution development
  • Develop and refine AI/GenAI architectures for client needs
  • Foster collaboration across data and analytics teams
  • Align with client objectives and industry standards
  • Promote technological advancements in data-driven solutions
View full posting on CareerOneStop → ID: 8b9a9c3e88cc
Principal Data Scientist
Maximus · Olympia, WA
Senior Master's
2026-05-09
Requirements
  • '- Bachelor's degree in related field required.
  • 10-12 years of relevant professional experience required.
  • Job-Specific Minimum Requirements (required skills that align with contract LCAT, verifiable, and measurable):
  • 10+ years of relevant Software Development + AI / ML / DS experience.
  • Professional Programming experience (e.g. Python, R, etc.).
  • Experience with AI / Machine Learning.
  • Experience working as a contributor on a team.
  • Experience leading AI/DS/or Analytics teams.
  • Experience mentoring Junior Staff.
  • Experience with program management.
Preferred
  • Master's in quantitative discipline (Math, Operations Research, Computer Science, etc.)
  • Experience developing machine learning or signal processing algorithms.
  • Ability to leverage mathematical principles to model new and novel behaviors.
  • Ability to leverage statistics to identify true signals from noise or clutter.
  • Experience working as an individual contributor in AI or modeling and simulation.
  • Use of state-of-the-art technology to solve operational problems in AI, Machine Learning, or Modeling and Simulation spheres.
  • Strong knowledge of data structures, common computing infrastructures/paradigms (stand alone and cloud), and software engineering principles.
  • Ability to design custom solutions in the AI and Advanced Analytics sphere for customers. This includes the ability to scope customer needs, identify currently existing technologies, and develop custom software solutions to fill any gaps in available off the shelf solutions.
  • Use and development of program automation, CI/CD, DevSecOps, and Agile.
  • Experience managing technical teams delivering technical solutions for clients.
  • Experience working with optimization problems like scheduling.
  • Experience with Data Analytics and Visualizations.
  • Cloud certifications (AWS, Azure, or GCP).
  • 10+ yrs of related experience in AI, advanced analytics, computer science, or software development.
Responsibilities
  • Make deep dives into the data, pulling out objective insights for business leaders.
  • Initiate, craft, and lead advanced analyses of operational data.
  • Provide a strong voice for the importance of data-driven decision making.
  • Provide expertise to others in data wrangling and analysis.
  • Convert complex data into visually appealing presentations.
  • Develop and deploy advanced methods to analyze operational data and derive meaningful, actionable insights for stakeholders and business development partners.
  • Understand the importance of automation and look to implement and initiate automated solutions where appropriate.
  • Initiate and take the lead on AI/ML initiatives as well as develop AI/ML code for projects.
  • Utilize various languages for scripting and write SQL queries. Serve as the primary point of contact for data and analytical usage across multiple projects.
  • Guide operational partners on product performance and solution improvement/maturity options.
  • Participate in intra-company data-related initiatives as well as help foster and develop relationships throughout the organization.
  • Learn new skills in advanced analytics/AI/ML tools, techniques, and languages.
  • Mentor more junior data analysts/data scientists as needed.
  • Apply strategic approach to lead projects from start to finish;
  • Develop, collaborate, and advance the applied and responsible use of AI, ML, simulation, and data science solutions throughout the enterprise and for our clients by finding the right fit of tools, technologies, processes, and automation to enable effective and efficient solutions for each unique situation.
  • Contribute and lead the creation, curation, and promotion of playbooks, best practices, lessons learned and firm intellectual capital.
  • Contribute to efforts across the enterprise to support the creation of solutions and real mission outcomes leveraging AI capabilities from Computer Vision, Natural Language Processing, LLMs and classical machine learning.
  • Maintain current knowledge and evaluation of the AI technology landscape and emerging developments and their applicability for use in production/operational environments.
View full posting on CareerOneStop → ID: c15502f20562
Manager, Data Science, Outbound Communications
Amazon · Seattle, WA
Manager Master's
2026-05-08
Requirements
  • 5+ years of building quantitative solutions as a scientist or science manager experience
  • 2+ years of scientists or machine learning engineers management experience
  • 5+ years of applying statistical models for large-scale application and building automated analytical systems experience
  • Master's degree in computer science, mathematics, statistics, machine learning or equivalent quantitative field
  • Knowledge of Python or R or other scripting language
Preferred
  • Experience in a least one area of Machine Learning (NLP, Regression, Classification, Clustering, or Anomaly Detection)
  • Experience with fairness in machine learning and artificial intelligence to detect and remove bias in ML/AI systems
Responsibilities
  • You will lead applied scientists, data scientists and business intelligence engineers to:
  • Optimize Outbound's inbox management and planning system to personalize frequency, send-time and relevance bar of our messages to customers.
  • Design and execute large-scale experiments such as multi-arm elasticity tests or RCTs to measure and improve incrementality/performance of our models.
  • Drive development of HVA propensity models (opt-out, purchase, etc.) to drive intended behavior of customers to their next stage of shopping and engagement with Amazon.
  • Drive AI-based transformation in data accuracy and reporting: migrating and enhancing the self-serve analytics capabilities developed by the team, automating WBR preparation, building anomaly detection, etc.
  • Own financial planning frameworks for outbound performance including QxG/HVE forecasting and ROI measurement for paid channel investments.
  • In addition, you will:
  • Hire, develop, and mentor scientists and BIEs while partnering cross-functionally with engineering, product, marketing, and partner science teams (CBA, P13N, CFV) to productionize solutions at scale.
  • Create, align and evolve your team's roadmap by prioritizing across multiple competing priorities using high judgement decisions.
View full posting on CareerOneStop → ID: 1db4bc78fe2e
AI & Machine Learning Engineering Consultant - Power & Utilities Sector - Manager - Consulting
EY · Seattle, WA
Manager Master's
2026-05-07
Requirements
  • A Bachelor's degree required (4-year degree).
  • 6-10 years of relevant experience of full-time working experience in AI, Data Science, and/or Machine Learning
  • 2-4 years of experience directly managing technical teams
  • Strong skills in Python
  • Ability lead, collaborate, and communicate effectively with diverse, hybrid and global teams
  • Experience designing, building, and maintaining high-impact, high-value production AI/ML solutions on a major cloud platform
  • Proficient in Generative AI models and frameworks (e.g., OpenAI, Dall-e, Langchain, Retrieval Augmented Generation (RAG)) and experienced with ML packages like scikit-learn and PyTorch
  • Experience with natural language processing and deep learning
  • Extensive experience in DevOps tools (GIT, Azure DevOps), Agile methodologies (Jira), and CI/CD pipelines for developing, deploying, and scaling analytical solutions
  • Experience with MLOps and ML workflows, including data ingestion, transformation, and evaluation
  • Experience with model retraining and feedback loop methodologies
  • Experience with model and solution monitoring and reporting
  • Understanding of data structures, data modelling and software engineering best practices
  • Strong foundation in mathematics, statistics, and operations research, with proficiency in data manipulation tools (SQL, Pandas, Spark) and deep learning techniques
  • Excellent communication skills for conveying findings and recommendations, with a willingness to travel for client engagements
  • Skills in Technical Design Optimization
  • Strong relationship-building skills
  • Demonstrated client trust and value
  • Digital fluency and emotional agility
  • Commercial acumen and negotiation skills
  • Proven ability to lead teams and manage change
  • Experience delivering analytics or AI solutions in asset-intensive environments (e.g., utilities, energy, infrastructure, manufacturing, or transportation) is strongly preferred.
  • Familiarity with utility regulatory, compliance, or operational data considerations is a plus.
  • *Ideally, you'll also have
  • A deep understanding of and ability to teach concepts, tools, features, functions, and benefits of different approaches to apply them
  • Master's degree Computer Science, Mathematics, Physical Sciences, or other quantitative field
  • Experience working with diverse teams to deliver complex solutions
  • Strong skills in languages beyond Python: R, JavaScript, Java, C++, C
  • Experience fine-tuning Generative AI models
  • Experience in managing complex projects with multiple stakeholders
  • A strong understanding of industry trends and emerging technologies
  • Skills in data visualization and storytelling with data
  • Experience with image processing techniques and/or speech and audio processing and analysis
  • Exposure to Power & Utilities transformation programs, such as grid modernization, advanced metering, wildfire mitigation, energy transition, DER integration, or digital operations initiatives.
  • Experience supporting executive-level decision-making in regulated environments, including preparation of materials that may be reviewed by regulators or governing bodies.
  • *What we look fo
  • We seek individuals who are not only technically proficient but also possess the ability to think critically and creatively. Top performers demonstrate a commitment to excellence, a collaborative spirit, and a passion for driving innovation in the field of AI and data science. Your ability to collaborate effectively and communicate with clarity will set you apart as a leader in our team.
  • In the Power & Utilities sector, we value leaders who can balance innovation with reliability, speed with safety, and advanced analytics with regulatory and operational realities delivering AI solutions that utilities can trust, scale, and defend.
Responsibilities
  • As a Manager in AI Native Engineering, you will play a pivotal role in delivering innovative solutions that drive business success. You will work with a wide variety of clients to deliver the latest data science and big data technologies. Your teams will design and build scalable solutions that unify, enrich, and derive insights from varied data sources across a broad technology landscape. You will help our clients navigate the complex world of modern data science, analytics, and software engineering. We'll look to you to provide guidance and perform technical development tasks to ensure data science solutions are properly engineered and maintained to support the ongoing business needs of our clients.
  • You will be joining a dynamic and interdisciplinary team of scientists and engineers who love to tackle the most challenging computational problems for our clients. We love to think creatively, build applications efficiently, and collaborate in both the ideation of solutions and the pursuit of new opportunities. Many on our team have advanced academic degrees or equivalent experience in industry.
  • In Power & Utilities contexts, this includes working with business, IT, and operations leaders to translate regulated utility priorities-such as safety, reliability, affordability, and compliance-into scalable AI-enabled solutions.
  • Leading workstream delivery and ensuring the effective management of processes and projects.
  • Continuously improving processes by identifying innovative solutions through research and analysis.
  • Managing professional employees and supervising teams to deliver complex technical initiatives, with accountability for performance and results.
  • Engaging actively with clients, participating in daily working sessions, and leading workstreams from planning through execution to closure.
  • Identifying opportunities for additional services and managing engagement economics.
  • Designing and delivering AI/ML use cases relevant to Power & Utilities, such as asset health and failure prediction, outage detection and restoration optimization, vegetation management analytics, demand forecasting, load and DER forecasting, predictive maintenance, customer operations optimization, and regulatory analytics.
  • Working with utility data sources including SCADA, AMI/AMI 2.0, GIS, EAM (e.g., Maximo), OMS, CIS, and historian systems, and integrating these into modern analytics platforms.
  • Supporting utilities in moving AI solutions from pilots to production while meeting regulatory, audit, cybersecurity, and data governance requirements.
  • *Skills and attributes for success
  • To excel in this role, you will need a blend of technical expertise and strong interpersonal skills. This role will work to deliver tech at speed, innovate at scale and put humans at the center. Provide technical guidance and share knowledge with team members with diverse skills and backgrounds. Consistently deliver quality client services focusing on more complex, judgmental and/or specialized issues surrounding emerging technology. Demonstrate technical capabilities and professional knowledge. Learn about EY and its service lines and actively assess and present ways to apply knowledge and services
  • For Power & Utilities clients, success also requires an understanding of regulated operating models, risk tolerance, safety culture, rate cases, capital programs, and long asset lifecycles, and the ability to align AI outcomes to these realities.
  • The following attributes will make a significant impact:
  • Proven ability to develop solutions to complex problems and recommend changes to policies and procedures.
  • Strong judgment in selecting methods and techniques for obtaining results.
  • Experience in managing client relationships and delivering high-quality service.
  • Ability to lead teams effectively and manage change within the organization.
  • Ability to translate AI and analytics outputs into business-relevant insights for utility executives, regulators, and operational leaders.
  • Comfort operating in highly regulated environments with strong governance, documentation, explainability, and model risk management expectations.
View full posting on CareerOneStop → ID: 686e59cf50a7
AI & Machine Learning Engineering Consultant - Power & Utilities Sector - Manager - Consulting
EY · Olympia, WA
Manager Master's
2026-05-07
Requirements
  • A Bachelor's degree required (4-year degree).
  • 6-10 years of relevant experience of full-time working experience in AI, Data Science, and/or Machine Learning
  • 2-4 years of experience directly managing technical teams
  • Strong skills in Python
  • Ability lead, collaborate, and communicate effectively with diverse, hybrid and global teams
  • Experience designing, building, and maintaining high-impact, high-value production AI/ML solutions on a major cloud platform
  • Proficient in Generative AI models and frameworks (e.g., OpenAI, Dall-e, Langchain, Retrieval Augmented Generation (RAG)) and experienced with ML packages like scikit-learn and PyTorch
  • Experience with natural language processing and deep learning
  • Extensive experience in DevOps tools (GIT, Azure DevOps), Agile methodologies (Jira), and CI/CD pipelines for developing, deploying, and scaling analytical solutions
  • Experience with MLOps and ML workflows, including data ingestion, transformation, and evaluation
  • Experience with model retraining and feedback loop methodologies
  • Experience with model and solution monitoring and reporting
  • Understanding of data structures, data modelling and software engineering best practices
  • Strong foundation in mathematics, statistics, and operations research, with proficiency in data manipulation tools (SQL, Pandas, Spark) and deep learning techniques
  • Excellent communication skills for conveying findings and recommendations, with a willingness to travel for client engagements
  • Skills in Technical Design Optimization
  • Strong relationship-building skills
  • Demonstrated client trust and value
  • Digital fluency and emotional agility
  • Commercial acumen and negotiation skills
  • Proven ability to lead teams and manage change
  • Experience delivering analytics or AI solutions in asset-intensive environments (e.g., utilities, energy, infrastructure, manufacturing, or transportation) is strongly preferred.
  • Familiarity with utility regulatory, compliance, or operational data considerations is a plus.
  • *Ideally, you'll also have
  • A deep understanding of and ability to teach concepts, tools, features, functions, and benefits of different approaches to apply them
  • Master's degree Computer Science, Mathematics, Physical Sciences, or other quantitative field
  • Experience working with diverse teams to deliver complex solutions
  • Strong skills in languages beyond Python: R, JavaScript, Java, C++, C
  • Experience fine-tuning Generative AI models
  • Experience in managing complex projects with multiple stakeholders
  • A strong understanding of industry trends and emerging technologies
  • Skills in data visualization and storytelling with data
  • Experience with image processing techniques and/or speech and audio processing and analysis
  • Exposure to Power & Utilities transformation programs, such as grid modernization, advanced metering, wildfire mitigation, energy transition, DER integration, or digital operations initiatives.
  • Experience supporting executive-level decision-making in regulated environments, including preparation of materials that may be reviewed by regulators or governing bodies.
  • *What we look fo
  • We seek individuals who are not only technically proficient but also possess the ability to think critically and creatively. Top performers demonstrate a commitment to excellence, a collaborative spirit, and a passion for driving innovation in the field of AI and data science. Your ability to collaborate effectively and communicate with clarity will set you apart as a leader in our team.
  • In the Power & Utilities sector, we value leaders who can balance innovation with reliability, speed with safety, and advanced analytics with regulatory and operational realities delivering AI solutions that utilities can trust, scale, and defend.
Responsibilities
  • As a Manager in AI Native Engineering, you will play a pivotal role in delivering innovative solutions that drive business success. You will work with a wide variety of clients to deliver the latest data science and big data technologies. Your teams will design and build scalable solutions that unify, enrich, and derive insights from varied data sources across a broad technology landscape. You will help our clients navigate the complex world of modern data science, analytics, and software engineering. We'll look to you to provide guidance and perform technical development tasks to ensure data science solutions are properly engineered and maintained to support the ongoing business needs of our clients.
  • You will be joining a dynamic and interdisciplinary team of scientists and engineers who love to tackle the most challenging computational problems for our clients. We love to think creatively, build applications efficiently, and collaborate in both the ideation of solutions and the pursuit of new opportunities. Many on our team have advanced academic degrees or equivalent experience in industry.
  • In Power & Utilities contexts, this includes working with business, IT, and operations leaders to translate regulated utility priorities-such as safety, reliability, affordability, and compliance-into scalable AI-enabled solutions.
  • Leading workstream delivery and ensuring the effective management of processes and projects.
  • Continuously improving processes by identifying innovative solutions through research and analysis.
  • Managing professional employees and supervising teams to deliver complex technical initiatives, with accountability for performance and results.
  • Engaging actively with clients, participating in daily working sessions, and leading workstreams from planning through execution to closure.
  • Identifying opportunities for additional services and managing engagement economics.
  • Designing and delivering AI/ML use cases relevant to Power & Utilities, such as asset health and failure prediction, outage detection and restoration optimization, vegetation management analytics, demand forecasting, load and DER forecasting, predictive maintenance, customer operations optimization, and regulatory analytics.
  • Working with utility data sources including SCADA, AMI/AMI 2.0, GIS, EAM (e.g., Maximo), OMS, CIS, and historian systems, and integrating these into modern analytics platforms.
  • Supporting utilities in moving AI solutions from pilots to production while meeting regulatory, audit, cybersecurity, and data governance requirements.
  • *Skills and attributes for success
  • To excel in this role, you will need a blend of technical expertise and strong interpersonal skills. This role will work to deliver tech at speed, innovate at scale and put humans at the center. Provide technical guidance and share knowledge with team members with diverse skills and backgrounds. Consistently deliver quality client services focusing on more complex, judgmental and/or specialized issues surrounding emerging technology. Demonstrate technical capabilities and professional knowledge. Learn about EY and its service lines and actively assess and present ways to apply knowledge and services
  • For Power & Utilities clients, success also requires an understanding of regulated operating models, risk tolerance, safety culture, rate cases, capital programs, and long asset lifecycles, and the ability to align AI outcomes to these realities.
  • The following attributes will make a significant impact:
  • Proven ability to develop solutions to complex problems and recommend changes to policies and procedures.
  • Strong judgment in selecting methods and techniques for obtaining results.
  • Experience in managing client relationships and delivering high-quality service.
  • Ability to lead teams effectively and manage change within the organization.
  • Ability to translate AI and analytics outputs into business-relevant insights for utility executives, regulators, and operational leaders.
  • Comfort operating in highly regulated environments with strong governance, documentation, explainability, and model risk management expectations.
View full posting on CareerOneStop → ID: d43ded705913
AI & Machine Learning Engineering Consultant - Power & Utilities Sector - Manager - Consulting
EY · Portland, OR
Manager Master's
2026-05-07
Requirements
  • A Bachelor's degree required (4-year degree).
  • 6-10 years of relevant experience of full-time working experience in AI, Data Science, and/or Machine Learning
  • 2-4 years of experience directly managing technical teams
  • Strong skills in Python
  • Ability lead, collaborate, and communicate effectively with diverse, hybrid and global teams
  • Experience designing, building, and maintaining high-impact, high-value production AI/ML solutions on a major cloud platform
  • Proficient in Generative AI models and frameworks (e.g., OpenAI, Dall-e, Langchain, Retrieval Augmented Generation (RAG)) and experienced with ML packages like scikit-learn and PyTorch
  • Experience with natural language processing and deep learning
  • Extensive experience in DevOps tools (GIT, Azure DevOps), Agile methodologies (Jira), and CI/CD pipelines for developing, deploying, and scaling analytical solutions
  • Experience with MLOps and ML workflows, including data ingestion, transformation, and evaluation
  • Experience with model retraining and feedback loop methodologies
  • Experience with model and solution monitoring and reporting
  • Understanding of data structures, data modelling and software engineering best practices
  • Strong foundation in mathematics, statistics, and operations research, with proficiency in data manipulation tools (SQL, Pandas, Spark) and deep learning techniques
  • Excellent communication skills for conveying findings and recommendations, with a willingness to travel for client engagements
  • Skills in Technical Design Optimization
  • Strong relationship-building skills
  • Demonstrated client trust and value
  • Digital fluency and emotional agility
  • Commercial acumen and negotiation skills
  • Proven ability to lead teams and manage change
  • Experience delivering analytics or AI solutions in asset-intensive environments (e.g., utilities, energy, infrastructure, manufacturing, or transportation) is strongly preferred.
  • Familiarity with utility regulatory, compliance, or operational data considerations is a plus.
  • *Ideally, you'll also have
  • A deep understanding of and ability to teach concepts, tools, features, functions, and benefits of different approaches to apply them
  • Master's degree Computer Science, Mathematics, Physical Sciences, or other quantitative field
  • Experience working with diverse teams to deliver complex solutions
  • Strong skills in languages beyond Python: R, JavaScript, Java, C++, C
  • Experience fine-tuning Generative AI models
  • Experience in managing complex projects with multiple stakeholders
  • A strong understanding of industry trends and emerging technologies
  • Skills in data visualization and storytelling with data
  • Experience with image processing techniques and/or speech and audio processing and analysis
  • Exposure to Power & Utilities transformation programs, such as grid modernization, advanced metering, wildfire mitigation, energy transition, DER integration, or digital operations initiatives.
  • Experience supporting executive-level decision-making in regulated environments, including preparation of materials that may be reviewed by regulators or governing bodies.
  • *What we look fo
  • We seek individuals who are not only technically proficient but also possess the ability to think critically and creatively. Top performers demonstrate a commitment to excellence, a collaborative spirit, and a passion for driving innovation in the field of AI and data science. Your ability to collaborate effectively and communicate with clarity will set you apart as a leader in our team.
  • In the Power & Utilities sector, we value leaders who can balance innovation with reliability, speed with safety, and advanced analytics with regulatory and operational realities delivering AI solutions that utilities can trust, scale, and defend.
Responsibilities
  • As a Manager in AI Native Engineering, you will play a pivotal role in delivering innovative solutions that drive business success. You will work with a wide variety of clients to deliver the latest data science and big data technologies. Your teams will design and build scalable solutions that unify, enrich, and derive insights from varied data sources across a broad technology landscape. You will help our clients navigate the complex world of modern data science, analytics, and software engineering. We'll look to you to provide guidance and perform technical development tasks to ensure data science solutions are properly engineered and maintained to support the ongoing business needs of our clients.
  • You will be joining a dynamic and interdisciplinary team of scientists and engineers who love to tackle the most challenging computational problems for our clients. We love to think creatively, build applications efficiently, and collaborate in both the ideation of solutions and the pursuit of new opportunities. Many on our team have advanced academic degrees or equivalent experience in industry.
  • In Power & Utilities contexts, this includes working with business, IT, and operations leaders to translate regulated utility priorities-such as safety, reliability, affordability, and compliance-into scalable AI-enabled solutions.
  • Leading workstream delivery and ensuring the effective management of processes and projects.
  • Continuously improving processes by identifying innovative solutions through research and analysis.
  • Managing professional employees and supervising teams to deliver complex technical initiatives, with accountability for performance and results.
  • Engaging actively with clients, participating in daily working sessions, and leading workstreams from planning through execution to closure.
  • Identifying opportunities for additional services and managing engagement economics.
  • Designing and delivering AI/ML use cases relevant to Power & Utilities, such as asset health and failure prediction, outage detection and restoration optimization, vegetation management analytics, demand forecasting, load and DER forecasting, predictive maintenance, customer operations optimization, and regulatory analytics.
  • Working with utility data sources including SCADA, AMI/AMI 2.0, GIS, EAM (e.g., Maximo), OMS, CIS, and historian systems, and integrating these into modern analytics platforms.
  • Supporting utilities in moving AI solutions from pilots to production while meeting regulatory, audit, cybersecurity, and data governance requirements.
  • *Skills and attributes for success
  • To excel in this role, you will need a blend of technical expertise and strong interpersonal skills. This role will work to deliver tech at speed, innovate at scale and put humans at the center. Provide technical guidance and share knowledge with team members with diverse skills and backgrounds. Consistently deliver quality client services focusing on more complex, judgmental and/or specialized issues surrounding emerging technology. Demonstrate technical capabilities and professional knowledge. Learn about EY and its service lines and actively assess and present ways to apply knowledge and services
  • For Power & Utilities clients, success also requires an understanding of regulated operating models, risk tolerance, safety culture, rate cases, capital programs, and long asset lifecycles, and the ability to align AI outcomes to these realities.
  • The following attributes will make a significant impact:
  • Proven ability to develop solutions to complex problems and recommend changes to policies and procedures.
  • Strong judgment in selecting methods and techniques for obtaining results.
  • Experience in managing client relationships and delivering high-quality service.
  • Ability to lead teams effectively and manage change within the organization.
  • Ability to translate AI and analytics outputs into business-relevant insights for utility executives, regulators, and operational leaders.
  • Comfort operating in highly regulated environments with strong governance, documentation, explainability, and model risk management expectations.
View full posting on CareerOneStop → ID: 8925bf24e604
Data Science Consultant
Deloitte · Seattle, WA
Mid-level Master's
2026-05-05
Requirements
  • A Bachelor's in a quantitative field (engineering, mathematics, physics, machine learning, statistics or computer science) are the ideal candidates.
  • At least 2+ years of industry experience outside of academia
  • Ability to travel 30%, on average, based on the work you do and the client and industries/sectors you serve
  • Must be legally authorized to work in the United States without the need for employer sponsorship now or at any time in the future
Preferred
  • A Master's in a quantitative field (engineering, mathematics, physics, machine learning, statistics or computer science) are the ideal candidates.
  • Good problem decomposition skills and autonomy when faced with solving data problems
  • Experience manipulating large marketing data sets and performing ETL
  • Excellent hands-on knowledge of modeling approaches such as Boosted Trees, Logistic regression, Classification Techniques, Unsupervised models, LLM, and experimental design
  • Experience with large data sets generated in the Ad Tech or Marketing technology spaces
  • Excellent verbal and written communication skills are required. Candidates must be proficient in conveying complex data insights in an accessible manner to a non-technical audience, including those outside the data science department. This entails adeptness in tailoring messages effectively and choosing appropriate visual aids to facilitate understanding.
  • Proficiency in high level scripting language, such as Python or R
  • Understanding of the strategic application of data science methodologies in driving valuable business outcomes for large enterprises
  • If you have code in the open domain (for example GitHub) or have written about AI/DS please share this with us
  • Experience with Deep Learning architectures and/or Reinforcement Learning
  • The wage range for this role takes into account the wide range of factors that are considered in making compensation decisions including but not limited to skill sets; experience and training; licensure and certifications; and other business and organizational needs. The disclosed range estimate has not been adjusted for the applicable geographic differential associated with the location at which the position may be filled. At Deloitte, it is not typical for an individual to be hired at or near the top of the range for their role and compensation decisions are dependent on the facts and circumstances of each case. A reasonable estimate of the current range is $93,000 to $171,300.
  • You may also be eligible to participate in a discretionary annual incentive program, subject to the rules governing the program, whereby an award, if any, depends on various factors, including, without limitation, individual and organizational performance.
View full posting on CareerOneStop → ID: 8fa5ec90c051
Data Scientist II, SCOT OSS - Sourcing Execution & Performance
Amazon · Bellevue, WA
Mid-level Master's
2026-05-02
Requirements
  • 2+ years of data scientist or similar role involving data extraction, analysis, statistical modeling and communication experience
  • 2+ years of data querying languages (e.g. SQL, Hadoop/Hive) experience
  • 3+ years of machine learning/statistical modeling data analysis tools and techniques, and parameters that affect their performance experience
  • Master's degree in a quantitative field, or Bachelor's degree and 5+ years of a quantitative field such as statistics, mathematics, data science, business analytics, economics, finance, engineering, or computer science experience
  • Experience applying theoretical models in an applied environment
Preferred
  • Experience in Python, Perl, or another scripting language
  • Experience in a ML or data scientist role with a large technology company
Responsibilities
  • Collaborate with product managers, science, and engineering teams to design and implement model solutions for Sourcing Execution & Performance systems
  • Use large datasets or experiments to make causal inferences or predictions
  • Work with engineers to automate science analysis processes and build scalable measurement solutions
  • Interpret data, write reports, and make actionable recommendations
  • Drive technical standards and best practices for the team's Science solutions
  • Mentor and provide technical guidance to other team members on complex projects
  • Amazon offers a full range of benefits that support you and eligible family members, including domestic partners and their children. Benefits can vary by location, the number of regularly scheduled hours you work, length of employment, and job status such as seasonal or temporary employment.
  • The benefits that generally apply to regular, full-time employees include:
  • Medical, Dental, and Vision Coverage
  • Maternity and Parental Leave Options
  • Paid Time Off (PTO)
  • If you are not sure that every qualification on the list above describes you exactly, we'd still love to hear from you!
  • At Amazon, we value people with unique backgrounds, experiences, and skillsets. If you're passionate about this role and want to make an impact on a global scale, please apply!
View full posting on CareerOneStop → ID: 7eca1a38e8a5
Data Scientist III - AMZ9971313
IMDB.COM, INC. · Seattle, WA
Mid-level Master's
2026-05-02

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

View full posting on CareerOneStop → ID: 41a7dcc4c83f
Manager III, Data Science - AMZ9749732
AMAZON WEB SERVICES, INC. · Seattle, WA
Manager Master's
2026-05-02

[MULTIPLE POSITIONS AVAILABLE]{.underline} [Employer]{.underline}: AMAZON WEB SERVICES, INC. [Offered Position]{.underline}: Manager III, Data Science [Job Location]{.underline}: Seattle, Washington [Job Number]{.underline}:

View full posting on CareerOneStop → ID: c3e6703f8053
Associate Data Scientist
Carnival Cruise Line · Seattle, WA
Entry-level Master's
2026-05-01
Requirements
  • Bachelor's or Master's degree in Mathematics, Statistics, Operations Research, Data Science, or a related numeric discipline.
  • Experience (internship or 0-2 years) in a data science, analytics, or quantitative modeling role (travel or revenue management industry experience a plus).
  • Technical proficiency in Python or R, and SQL/relational databases.
  • Familiarity with forecasting, optimization, and statistical modeling techniques.
  • Strong communication and interpersonal skills, with the ability to explain complex concepts to non-technical audiences.
  • Professionalism, reliability, and a collaborative approach to teamwork
  • At least 2 years experience in a data scientist role, preferably within the travel industry
  • Experience within Revenue Management
  • Experience in Systems development a plus, with technical expertise in R or Python, and SQL / relational databases
  • Travel: No or very little travel likely
  • Work Conditions: Work primarily in a climate-controlled environment with minimal safety/health hazard potential.
  • Physical Demands: Must be able to remain in a stationary position at a desk and/or computer for extended periods of time.
  • This position is classified as "in-office." As an in-office role, it requires employees to work from Holland America's office in Seattle Monday through Thursday each week.
  • *What You Can Expect
  • Cruise and Travel Privileges for You and Your Family
  • Health Benefits
  • Employee Stock Purchase Plan
  • Training & Professional Development
  • Tuition & Professional Certification Reimbursement
  • Base Hourly Range: $28.46 to $38.41. The range is applicable for the labor market where the role is intended to be hired. Final base salary is directly related to each candidate's qualifications and experience uniquely.
Responsibilities
  • Holland America Line has been exploring the world since 1873. Our ships offer innovative features and enriching experiences focused on destination exploration and personalized travel, inviting guests to savor the journey.
  • The Associate Data Scientist will play a hands-on role in supporting the ongoing development, enhancement, and adoption of YODA-the proprietary yield optimization and demand analytics platform built and owned by the data science teams across Carnival Corporation. You will work closely with the Revenue Management (RM) teams across Holland America Line and Seabourn, ensuring YODA's models and analytics are accurate, accessible, and actionable for end users. Your work will help RM teams make better, data-driven decisions and maximize net revenue and profitability.
  • Here's a summary of what Holland America Line is looking for. Is this you?
  • Serve as a primary point of contact for RM teams, providing day-to-day support, troubleshooting, and guidance on YODA's features and outputs.
  • Scope and Develop models as appropriate to support day-to-day pricing and inventory decisions and operations. Help interpret model outputs and analytics for non-technical stakeholders, supporting improved price and inventory decisions.
  • Gather feedback from end users, translate business questions into analytical tasks, and ensure YODA's tools are well understood and effectively adopted.
  • Assist in building, validating, and updating forecasting and optimization models within YODA, including price elasticity, booking materialization, cancellation/retention, constraining, and segmentation models. Communicate model updates and implications clearly to RM teams, ensuring transparency and trust in the analytics.
  • Work closely with the Revenue Science Manager, BI, and ML Ops teams to feed advanced analytics into YODA and associated reporting/alerting systems.
  • Recommend and help implement enhancements to YODA's toolset and functionality based on user feedback and business needs.
  • Own YODA release testing for the brands, ensuring all models and changes applied work for the RM teams.
  • Maintain clear, user-friendly documentation and training materials for YODA.
  • Support the onboarding and upskilling of RM team members, helping them build confidence and proficiency in using advanced analytics tools.
  • *Knowledge & Skills:
  • Scope: Supports the ongoing development, enhancement, and user adoption of the YODA revenue management analytics platform, working directly with Revenue Management teams across Holland America Line and Seabourn to ensure all models and tools are accurate, accessible, and actionable.
  • Problem solving: Translates business questions and operational challenges from RM teams into analytical tasks, troubleshooting model outputs, and adapting forecasting and optimization approaches to meet evolving commercial needs.
  • Impact: Enables data-driven, timely, and profitable pricing and inventory decisions by ensuring YODA delivers reliable forecasts and insights, directly supporting the commercial success of both brands. The Junior Data Scientist will materially improve the accuracy and adoption levels of YODA and work with the Revenue Science Manager to ensure YODA continues to develop to meet the evolving needs of the brands
  • Leadership: Demonstrates initiative by proactively engaging with end users, sharing knowledge, and helping to build analytical capability within the RM teams through clear communication, training, and collaborative problem solving.
View full posting on CareerOneStop → ID: 65a484c016ed
Data Scientist, SPX AI Lab, SPX Science
Amazon · Seattle, WA
Mid-level Master's
2026-05-01
Requirements
  • 2+ years of data scientist experience
  • 3+ years of data querying languages (e.g. SQL), scripting languages (e.g. Python) or statistical/mathematical software (e.g. R, SAS, Matlab, etc.) experience
  • 3+ years of machine learning/statistical modeling data analysis tools and techniques, and parameters that affect their performance experience
  • 1+ years of working with or evaluating AI systems experience
  • Master's degree in Science, Technology, Engineering, or Mathematics (STEM), or experience working in Science, Technology, Engineering, or Mathematics (STEM)
Preferred
  • Knowledge of machine learning concepts and their application to reasoning and problem-solving
  • Experience in a ML or data scientist role with a large technology company
  • Experience in defining and creating benchmarks for assessing GenAI model performance
  • Experience working on multi-team, cross-disciplinary projects
  • Experience applying quantitative analysis to solve business problems and making data-driven business decisions
  • Experience effectively communicating complex concepts through written and verbal communication
Responsibilities
  • Own the product vision, strategy, and roadmap for a key Seller Assistant capability area.
  • Define and ship agentic experiences - reasoning, planning, memory, context engineering - that solve hard seller problems at scale.
  • Partner with scientists and engineers to translate frontier AI research into production-grade features sellers trust and depend on.
  • Design rigorous evaluation frameworks - automated and human-in-the-loop - to measure agent quality, accuracy, and business impact.
  • Deep-dive into seller data, identify unmet needs, and write compelling PRFAQs that set the direction for your team.
  • Drive cross-functional alignment across science, engineering, UX, and business teams to deliver with speed and quality.
View full posting on CareerOneStop → ID: afc613081312
Principal Data Scientist, Prime Video
Amazon · Seattle, WA
Senior Master's
2026-05-01
Requirements
  • Bachelors' degree in Statistics, Applied Math, Operations Research, Economics, or a related quantitative field
  • 11+ years of data scientist experience
  • Competency in data querying languages (e.g. SQL) and scripting languages (e.g. Python)
  • Experience with statistical models (e.g., logistic regression. supervised learning approaches)
  • Experience with online experimentation systems
Preferred
  • Masters Degree in Data Science or related field
  • Experience designing and building large-scale online measurement systems
  • Experience establishing Bayesian decision frameworks for business decisions
  • Excellent communications with non-technical executive audiences
Responsibilities
  • Define and drive the multi-year vision for experiment-based measurement systems within Prime Video
  • Partner with product stakeholders and science peers to identify strategic data-driven opportunities to improve the customer experience
  • Communicate findings, conclusions, and recommendations to technical and non-technical business leaders across Prime Video
  • Educate senior leaders about and advocate for high-quality measurement as an input to data-driven decisions
  • Mentor junior scientists and review technical artifacts to ensure quality
  • Stay up-to-date on the latest data science tools, techniques, and best practices and help evangelize them across the organization
View full posting on CareerOneStop → ID: a9d20ec7f26c
Sr. Data Scientist, Field Engineering
Amazon · Bellevue, WA
Senior Master's
2026-05-01
Requirements
  • 5+ years of data querying languages (e.g. SQL), scripting languages (e.g. Python) or statistical/mathematical software (e.g. R, SAS, Matlab, etc.) experience
  • 4+ years of data scientist or similar role involving data extraction, analysis, statistical modeling and communication experience
  • Master's degree in a quantitative field such as Statistics, Mathematics, Data Science, Business Analytics, Economics, Engineering, or Computer Science; OR Bachelor's degree and 8+ years of professional experience in a quantitative role.
Preferred
  • 2+ years of data visualization using AWS QuickSight, Tableau, R Shiny, etc. experience
  • Experience documenting modeling for technical and business leaders
  • Experience working with data engineers and business intelligence engineers collaboratively
  • Knowledge of AWS tech stack (e.g., AWS Redshift, S3, EC2, Glue)
  • Experience developing operational processes and data insights
  • Experience with anomaly detection, predictive maintenance, or reliability modeling in industrial or infrastructure contexts.
Responsibilities
  • Develop and maintain scalable models and analytical frameworks to measure and predict data center fleet performance, including availability, efficiency, and reliability KPIs across the global AWS infrastructure portfolio.
  • Apply advanced statistical and machine learning techniques to extract actionable insights from complex, large-scale operational datasets generated by data center systems (power, cooling, controls, etc.).
  • Partner with Field Engineers, Operations, and Portfolio Managers to identify high-impact opportunities for capacity and availability improvement, translating engineering domain knowledge into quantitative problem formulations.
  • Design and implement end-to-end data science workflows - from data acquisition and cleaning through model development, validation, and production deployment - enabling repeatable, scalable analysis.
  • Formalize assumptions about how data center systems are expected to perform and develop methods to systematically identify deviations, root causes, and high-ROI improvement opportunities.
  • Build self-service datasets, dashboards, and reporting mechanisms that provide Field Engineering leadership with real-time visibility into fleet health and portfolio performance.
  • Prepare narratives and data-driven recommendations for executive leadership that articulate decision points relative to fleet investment, risk trade-offs, and strategic priorities.
  • Collaborate with applied science, software engineering, and data engineering teams to ensure models integrate seamlessly with upstream and downstream systems.
View full posting on CareerOneStop → ID: 5532d33a9fd0
Sr. Data Scientist, Field Engineering
Amazon · Seattle, WA
Senior Master's
2026-05-01
Requirements
  • 5+ years of data querying languages (e.g. SQL), scripting languages (e.g. Python) or statistical/mathematical software (e.g. R, SAS, Matlab, etc.) experience
  • 4+ years of data scientist or similar role involving data extraction, analysis, statistical modeling and communication experience
  • Master's degree in a quantitative field such as Statistics, Mathematics, Data Science, Business Analytics, Economics, Engineering, or Computer Science; OR Bachelor's degree and 8+ years of professional experience in a quantitative role.
Preferred
  • 2+ years of data visualization using AWS QuickSight, Tableau, R Shiny, etc. experience
  • Experience documenting modeling for technical and business leaders
  • Experience working with data engineers and business intelligence engineers collaboratively
  • Knowledge of AWS tech stack (e.g., AWS Redshift, S3, EC2, Glue)
  • Experience developing operational processes and data insights
  • Experience with anomaly detection, predictive maintenance, or reliability modeling in industrial or infrastructure contexts.
Responsibilities
  • Develop and maintain scalable models and analytical frameworks to measure and predict data center fleet performance, including availability, efficiency, and reliability KPIs across the global AWS infrastructure portfolio.
  • Apply advanced statistical and machine learning techniques to extract actionable insights from complex, large-scale operational datasets generated by data center systems (power, cooling, controls, etc.).
  • Partner with Field Engineers, Operations, and Portfolio Managers to identify high-impact opportunities for capacity and availability improvement, translating engineering domain knowledge into quantitative problem formulations.
  • Design and implement end-to-end data science workflows - from data acquisition and cleaning through model development, validation, and production deployment - enabling repeatable, scalable analysis.
  • Formalize assumptions about how data center systems are expected to perform and develop methods to systematically identify deviations, root causes, and high-ROI improvement opportunities.
  • Build self-service datasets, dashboards, and reporting mechanisms that provide Field Engineering leadership with real-time visibility into fleet health and portfolio performance.
  • Prepare narratives and data-driven recommendations for executive leadership that articulate decision points relative to fleet investment, risk trade-offs, and strategic priorities.
  • Collaborate with applied science, software engineering, and data engineering teams to ensure models integrate seamlessly with upstream and downstream systems.
View full posting on CareerOneStop → ID: 7df92be0b7af
Machine Learning Engineer (multiple openings)
ADOBE SYSTEMS INC · Seattle, WA
Mid-level Master's
2026-05-01

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

View full posting on CareerOneStop → ID: 8335434df4e6
Machine Learning Engineer, Video Search Team
Apple · Seattle, WA
Mid-level Master's
2026-04-29
Requirements
  • 4+ years of industry or practical experience in machine learning, NLP, IR, or more recently Large Language Model ( LLMs).
  • Strong programming skills in Python, Java and Go for building scalable ML systems.
  • Hands-on expertise in ML libraries such as PyTorch, JAX, TensorFlow for model training and deployment.
  • Ability to translate product goals into technical solutions, improving user experience.
  • Strong communication, collaboration, and analytical problem-solving skills.
  • In-depth knowledge of search and information retrieval fundamentals, including indexing and ranking. Experience with retrieval and ranking algorithms and building big data pipelines using Hadoop, Java, Scala, Spark and more.
  • Industrial experience in search, classification, recommendation systems, or related fields.
  • Familiarity with A/B testing and data-driven product development.
  • Passionate about creating products loved by customers at Apple.
  • Master's degree or higher (or equivalent practical experience) in Computer Science, Machine Learning, Natural Language Processing, Artificial Intelligence, or a related field.
Preferred
  • Experience with search or recommendation systems, and semantic retrieval or vector databases.
  • Expertise in transformer architectures, embeddings, and retrieval or ranking models.
  • Experience in applying or fine-tuning LLMs for understanding and generation tasks. Familiarity with prompt design, context management, RAG and Agentic architectures and solutions.
  • Exposure to evaluation and safety frameworks for LLM-based systems.
  • Knowledge of reinforcement learning and other modern post training practices for LLMs.
  • Passion for developing intelligent, human-centered experiences to enhance content discovery.
Responsibilities
  • The Apple Services Engineering AI/ML organization is hiring a Machine Learning Engineer to join the Video Search team.
  • Our team builds the core intelligence that powers search discovery experiences in the Apple TV App, Siri, and Spotlight cross platforms, helping users effortlessly find and enjoy the content they love. We are a collaborative, high-impact team that values innovation, craftsmanship, and end-to-end ownership from idea to launch. Our systems combine large-scale data, modern retrieval and ranking models, and a deep commitment to user privacy.
  • Join us, you'll develop scalable systems and machine learning models that drive search relevance, personalization, and understanding of content at scale. Working closely with cross-functional partners in product and design, you'll translate cutting-edge research in advanced machine learning and generative AI into secure and delightful production features used by millions every day.
  • As a Machine Learning Engineer on the Video Search team, within the Apple Services Engineering AI/ML organization, you will design and deploy large-scale ML systems that power search and discovery across Apple platforms.
  • You'll apply machine learning, natural language understanding, and generative AI to model user intent and deliver relevant, personalized results. Your work will involve building and optimizing cutting edge data processing, ML models, retrieval pipelines, and ranking systems that operate at global scale and under strict privacy standards.
  • This is a hands-on role where you will collaborate closely with cross-functional teams to bring advanced ML technologies into production-shaping how users discovery content they love in Apple TV app, cross Apple TV partners on Apple Platforms, also through Siri and Spotlight.
View full posting on CareerOneStop → ID: 455b17ba2d5c
Staff Business Data Scientist, Google Cloud Marketing
Google · Kirkland, WA
Senior Master's
2026-04-29
Requirements
  • Master's degree in a quantitative discipline such as Statistics, Engineering, Sciences, or equivalent practical experience.
  • 7 years of experience using analytics to solve product or business problems, coding (e.g., Python, R, SQL), querying databases or statistical analysis.
  • Experience deploying ML models into production environments.
Preferred
  • 9 years of experience using analytics to solve product or business problems, coding (e.g., Python, R, SQL), querying databases or statistical analysis.
  • Experience with Machine Learning Operations (MLOps) tools and practices.
  • Understanding of business-to-business (B2B) enterprise SaaS business cycles, demand generation funnels, and marketing technology stacks.
Responsibilities
  • Google's leadership team hand-picks thorny business challenges, and members of BizOps work in small teams to find solutions. As part of this team you fully immerse yourself in data collection, draw insight from analysis, and then zoom out to develop compelling, synthesized recommendations. Taking strategy one step further, you also persuasively communicate your recommendations to senior-level executives, roll-up your sleeves to help drive implementation and check back-in to see the impact of your recommendations.
  • As a Staff Business Data Scientist, you will serve as a full-stack technical lead, owning the end-to-end life-cycle of data science products that drive Google Cloud's marketing and Go-to-market (GTM) strategy and measurement. You will move beyond traditional analysis to architect and build scalable intelligence systems.
  • In this role, you will bridge the gap between data engineering and data science. You will build the infrastructure required to ingest and process massive datasets, develop predictive models (e.g., lead scoring, propensity predictions), and engineer the Application Programming Interfaces (APIs) or serving layers that integrate these insights directly into our marketing measurement and tech stack. You will have a specific mandate to leverage Google's Generative AI capabilities and will utilize Large Language Models (LLMs) and Gemini models to engineer novel data science products that enhance our predictive capabilities. You will advocate for software engineering best practices within the data science team, ensuring our code is testable and maintainable. You will work with Marketing leadership to ensure the intelligence systems you build actively influence decision-making. You will also mentor data scientists on the team and advocate for statistical methodology and coding standards across the organization.
  • The US base salary range for this full-time position is $192,000-$278,000 + bonus + equity + benefits. Our salary ranges are determined by role, level, and location. Within the range, individual pay is determined by work location and additional factors, including job-related skills, experience, and relevant education or training. Your recruiter can share more about the specific salary range for your preferred location during the hiring process.
  • Please note that the compensation details listed in US role postings reflect the base salary only, and do not include bonus, equity, or benefits. Learn more aboutbenefits at Google (https://careers.google.com/benefits/) .
  • Lead the full Machine Learning (ML) life-cycle from data extraction and feature engineering to model training, validation, and deployment for critical marketing capabilities. Design and build ML models that solve ambiguous business problems and optimize the full customer life-cycle and demand funnel.
  • Design scalable data science applications using Google's LLM models to unlock insights from structured and unstructured data, build intelligent marketing agents, and automate decision-making processes within the Business-to-Business (B2B) funnel.
  • Define coding standards and engineering best practices for the team; mentor other data scientists on writing production-quality code and designing scalable architectures.
  • Partner with engineering and cross-functional data science teams to integrate model outputs directly into our martech systems, ensuring insights drive automated action.
  • Translate data science outputs into clear, actionable business recommendations for Director and Vice President level stakeholders.
  • Information collected and processed as part of your Google Careers profile, and any job applications you choose to submit is subject to Google'sApplicant and Candidate Privacy Policy (./privacy-policy) .
View full posting on CareerOneStop → ID: 4c7663329442
Staff Business Data Scientist, Google Cloud Marketing
Google · Seattle, WA
Senior Master's
2026-04-29
Requirements
  • Master's degree in a quantitative discipline such as Statistics, Engineering, Sciences, or equivalent practical experience.
  • 7 years of experience using analytics to solve product or business problems, coding (e.g., Python, R, SQL), querying databases or statistical analysis.
  • Experience deploying ML models into production environments.
Preferred
  • 9 years of experience using analytics to solve product or business problems, coding (e.g., Python, R, SQL), querying databases or statistical analysis.
  • Experience with Machine Learning Operations (MLOps) tools and practices.
  • Understanding of business-to-business (B2B) enterprise SaaS business cycles, demand generation funnels, and marketing technology stacks.
Responsibilities
  • Google's leadership team hand-picks thorny business challenges, and members of BizOps work in small teams to find solutions. As part of this team you fully immerse yourself in data collection, draw insight from analysis, and then zoom out to develop compelling, synthesized recommendations. Taking strategy one step further, you also persuasively communicate your recommendations to senior-level executives, roll-up your sleeves to help drive implementation and check back-in to see the impact of your recommendations.
  • As a Staff Business Data Scientist, you will serve as a full-stack technical lead, owning the end-to-end life-cycle of data science products that drive Google Cloud's marketing and Go-to-market (GTM) strategy and measurement. You will move beyond traditional analysis to architect and build scalable intelligence systems.
  • In this role, you will bridge the gap between data engineering and data science. You will build the infrastructure required to ingest and process massive datasets, develop predictive models (e.g., lead scoring, propensity predictions), and engineer the Application Programming Interfaces (APIs) or serving layers that integrate these insights directly into our marketing measurement and tech stack. You will have a specific mandate to leverage Google's Generative AI capabilities and will utilize Large Language Models (LLMs) and Gemini models to engineer novel data science products that enhance our predictive capabilities. You will advocate for software engineering best practices within the data science team, ensuring our code is testable and maintainable. You will work with Marketing leadership to ensure the intelligence systems you build actively influence decision-making. You will also mentor data scientists on the team and advocate for statistical methodology and coding standards across the organization.
  • The US base salary range for this full-time position is $192,000-$278,000 + bonus + equity + benefits. Our salary ranges are determined by role, level, and location. Within the range, individual pay is determined by work location and additional factors, including job-related skills, experience, and relevant education or training. Your recruiter can share more about the specific salary range for your preferred location during the hiring process.
  • Please note that the compensation details listed in US role postings reflect the base salary only, and do not include bonus, equity, or benefits. Learn more aboutbenefits at Google (https://careers.google.com/benefits/) .
  • Lead the full Machine Learning (ML) life-cycle from data extraction and feature engineering to model training, validation, and deployment for critical marketing capabilities. Design and build ML models that solve ambiguous business problems and optimize the full customer life-cycle and demand funnel.
  • Design scalable data science applications using Google's LLM models to unlock insights from structured and unstructured data, build intelligent marketing agents, and automate decision-making processes within the Business-to-Business (B2B) funnel.
  • Define coding standards and engineering best practices for the team; mentor other data scientists on writing production-quality code and designing scalable architectures.
  • Partner with engineering and cross-functional data science teams to integrate model outputs directly into our martech systems, ensuring insights drive automated action.
  • Translate data science outputs into clear, actionable business recommendations for Director and Vice President level stakeholders.
  • Information collected and processed as part of your Google Careers profile, and any job applications you choose to submit is subject to Google'sApplicant and Candidate Privacy Policy (./privacy-policy) .
View full posting on CareerOneStop → ID: e99b5c7a3917
Sr Data Scientist
T-Mobile USA, Inc · Bellevue, WA
Senior Master's
2026-04-29
Requirements
  • 4-7 years of industry experience in predictive modeling, data science, and analysis in an ML engineer or data scientist role building and deploying ML models or hands on experience developing deep learning models (Required)
  • 4-7 years of experience with data scripting languages (e.g., SQL, Python, R) (Required)
  • 4-7 years of Experience articulating and translating business questions and using statistical techniques to arrive at an answer using available data (Required)
  • 4-7 years of experience in data visualization (Required)
  • 4-7 years of experience working with relational database using SQL (Required)
  • 2-4 years of experience with big data architecture and pipeline, Hadoop, Hive, Spark, Kafka, etc. (Required)
  • 2-4 years of experience in the telecom industry preferred
  • *Knowledge, Skills and Abilities:
  • Mathematics : Calculus, linear algebra, statistics, and probability
  • Programming : Expertise in Python and SQL
  • Machine Learning: Expertise applying machine learning concepts and techniques related to supervised and unsupervised learning
  • Communication : Strong communication skills, ability to work with cross functional teams
  • Machine Learning: Expertise applying machine learning concepts and techniques related to supervised and
Education
  • Bachelor's Degree in Quantitative Discipline (math, statistics, economics, computer science, physics, engineering, etc.) Required
  • Masters Degree in Quantitative Discipline (math, statistics, economics, computer science, physics, engineering) Preferred.
Responsibilities
  • Extract, prepare and model large, complex data sets using a combination of skills, including machine learning theory, mathematics, statistics, and programming.
  • Deliver on-time quality analysis, interpretation, and synthesis of data into effective, concise, and actionable recommendations that enable intelligent decisioning for the company.
  • Provide senior-level guidance and mentorship to the data science team, including reviewing projects, models, and code for peers and junior team members.
  • Work with engineering teams to implement and improve machine learning pipelines and production-ready models.
  • Effectively communicate important information and insights to business leaders using verbal, written, and data visualization skills.
  • Also responsible for other Duties/Projects as assigned by business management as needed.
View full posting on CareerOneStop → ID: 0e173eaaf7b1
Senior Research Data Scientist
The Boeing Company · Seattle, WA
Senior Master's
2026-04-28
Requirements
  • Master's degree or higher in a quantitative field such as Data Science, Statistics, Economics, Operations Research, Machine Learning, Engineering, Industrial Organizational Psychology, Organizational Behavior, Psychometrics, Sociology, or a related discipline
  • 5+ years of experience in data science, quantitative research science, or data analytics
  • 5+ years of experience with the following data analytics methods Machine Learning, Simulation, Statistics, Data Mining, Regression, Survival Analysis, Time series models
  • 5+ years of experience in data analysis algorithms (e.g. data mining, statistics, machine learning, natural language processing, text mining, visual analytics) and building Descriptive, Predictive and Prescriptive models
  • 5+ years of experience in database management, programming, statistical modeling and/or machine learning (SQL, R, Python, JMP, Tableau, etc.)
  • Experience in Business Intelligence/data analytics tools (Microsoft Power BI, Dashboards, SQL, Tableau, etc.)
  • This is not an Export Control position.
Preferred
  • 10+ years of industry experience
  • Experience with HR systems and employee data environments
  • Experience applying AI to automate, accelerate, or optimize analytics, research, or reporting workflows
  • Experience with employee engagement, culture, leadership, talent, or organizational effectiveness research
  • Experience applying machine learning models from ideation through monitoring and maintenance
  • Capability to present highly technical information to nontechnical audiences
  • Capability to influence senior leaders on strategy, trade-offs, and policy decisions using evidence-based recommendations
  • Experience applying leading AI techniques and libraries to solve complex business problems and deliver measurable results
  • Strong visualization skills and experience creating compelling charts, dashboards, and executive summaries
  • Experience teaching, mentoring, and developing others
  • *Conflict of Interest:
  • Successful candidates for this job must satisfy the Company's Conflict of Interest (COI) assessment process.
Education
  • Master's Degree or Equivalent Required
Responsibilities
  • At Boeing, we innovate and collaborate to make the world a better place. We're committed to fostering an environment for every teammate that's welcoming, respectful and inclusive, with great opportunity for professional growth. Find your future with us.
  • Boeing's Global Talent, Development and Employee Experience organization has an exciting opportunity for a Senior Research Data Scientist to join the Employee Listening, Organizational Research, and Talent Assessment Team in Seattle, WA . The person in this role will lead deep dive analysis of employee survey, assessment, and workforce data, uncover meaningful organizational insights, and translate complex findings into compelling executive level narratives. This role sits at the intersection of research, analytics, strategy, and storytelling, ideal for someone who thrives on turning data into action and influencing senior leaders with clarity and confidence. You will help set the long-term research roadmap, defining measurement frameworks and success metrics, and establish standards for scientific rigor, reproducibility, practical and responsible use of AI/ML.
  • In this role, you will analyze large and complex datasets from surveys, assessments, HR systems, and business sources to generate actionable insights that inform organizational strategy, talent decisions, and employee experience improvements. You will lead mixed methods research, apply advanced statistical and predictive analytics, and use both structured and unstructured data to identify business trends, drivers, risks, and opportunities.
  • You will partner with executive leaders, HR, talent, and business teams to frame research questions, synthesize findings, and shape decisions through high impact reporting and storytelling. The ideal candidate combines strong technical expertise with the ability to simplify complex information, influence stakeholders, and help leaders understand the "so what" behind the data.
  • Lead advanced analysis of organizational survey, assessment, and workforce data to identify trends, drivers, risks, and opportunities
  • Design and execute research approaches to answer complex business and organizational questions using survey, assessment, interview, and workforce data
  • Translate ambiguous data into decision-ready executive syntheses, including recommendations, options, trade-offs, risks, and implementation considerations
  • Develop high-impact executive reports, presentations, and dashboards that tell a compelling data story
  • Partner with leaders, HR, talent, and business teams to define research questions and inform strategy
  • Synthesize multiple data sources, including surveys, assessments, open-ended feedback, internal business outcome metrics, and external benchmarks
  • Apply advanced statistical analysis, machine learning, and predictive modeling to surface insights and forecast outcomes
  • Advance NLP methods, including sentiment analysis, topic modeling, and entity recognition, to analyze unstructured text data
  • Conduct qualitative analysis, including coding, thematic analysis, and content analysis, to derive insights from narrative data
  • Ensure scientific rigor, validity, and reproducibility across all research and analytics through documented methods, version-controlled code, QA checks, and peer review
  • Present findings to senior stakeholders with confidence, clarity, and influence
  • Improve research methodologies, reporting standards, and storytelling approaches
  • Provide technical leadership, guidance, and mentoring to cross-functional partners and teammates
  • Identify and implement practical AI use cases that streamline workflows, automate repetitive tasks, improve analytical efficiency, and scale research output
  • Partner with other scientists to build team capability through coaching, documentation, and examples of effective day-to-day AI use
View full posting on CareerOneStop → ID: 3060b2231a4c
Data Scientist, SPX AI Lab, SPX Science
Amazon · Seattle, WA
Mid-level Master's
2026-04-25
Requirements
  • 2+ years of data scientist experience
  • 3+ years of data querying languages (e.g. SQL), scripting languages (e.g. Python) or statistical/mathematical software (e.g. R, SAS, Matlab, etc.) experience
  • 3+ years of machine learning/statistical modeling data analysis tools and techniques, and parameters that affect their performance experience
  • 1+ years of working with or evaluating AI systems experience
  • Master's degree in Science, Technology, Engineering, or Mathematics (STEM), or experience working in Science, Technology, Engineering, or Mathematics (STEM)
Preferred
  • Knowledge of machine learning concepts and their application to reasoning and problem-solving
  • Experience in a ML or data scientist role with a large technology company
  • Experience in defining and creating benchmarks for assessing GenAI model performance
  • Experience working on multi-team, cross-disciplinary projects
  • Experience applying quantitative analysis to solve business problems and making data-driven business decisions
  • Experience effectively communicating complex concepts through written and verbal communication
Responsibilities
  • - Respond to Seller feedback and implement fix in Gen AI solution to enhance Seller experience
  • - Drive deep-dive analytical studies to understand seller pain points, evaluate feature performance, and identify opportunities to improve the Selling Partner experience.
  • - Design and execute robust causal inference and measurement frameworks, including A/B testing, quasi-experiments, and observational causal methods (e.g., diff-in-diff, synthetic control, propensity score methods).
  • - Develop scalable analytical pipelines for impact measurement, KPI development, metric integrity validation, and long-term business monitoring.
  • - Apply NLP and statistical modeling techniques-including topic modeling, clustering, semantic similarity, and classification-to uncover insights from unstructured seller interactions, feedback, and content.
  • - Partner with scientists, engineers, economists, and product managers to translate ambiguous problems into structured analytical approaches and influence product roadmaps with data-driven recommendations.
  • - Build and maintain automated analytics tools and dashboards to democratize insights for product, science, and engineering teams.
  • - Collaborate scientists to evaluate model-driven features, quantify impact, and ensure mechanisms are grounded in rigorous measurement.
  • - Research and experiment with new analytical and measurement methodologies, ensuring Amazon leverages the latest best practices in causal inference, NLP, and GenAI.
View full posting on CareerOneStop → ID: c879768837cc
Data Scientist, SPX AI Lab, SPX Science
Amazon · Seattle, WA
Mid-level Master's
2026-04-25
Requirements
  • 2+ years of data scientist experience
  • 3+ years of data querying languages (e.g. SQL), scripting languages (e.g. Python) or statistical/mathematical software (e.g. R, SAS, Matlab, etc.) experience
  • 3+ years of machine learning/statistical modeling data analysis tools and techniques, and parameters that affect their performance experience
  • 1+ years of working with or evaluating AI systems experience
  • Master's degree in Science, Technology, Engineering, or Mathematics (STEM), or experience working in Science, Technology, Engineering, or Mathematics (STEM)
Preferred
  • Knowledge of machine learning concepts and their application to reasoning and problem-solving
  • Experience in a ML or data scientist role with a large technology company
  • Experience in defining and creating benchmarks for assessing GenAI model performance
  • Experience working on multi-team, cross-disciplinary projects
  • Experience applying quantitative analysis to solve business problems and making data-driven business decisions
  • Experience effectively communicating complex concepts through written and verbal communication
Responsibilities
  • - Respond to Seller feedback and implement fix in Gen AI solution to enhance Seller experience
  • - Drive deep-dive analytical studies to understand seller pain points, evaluate feature performance, and identify opportunities to improve the Selling Partner experience.
  • - Design and execute robust causal inference and measurement frameworks, including A/B testing, quasi-experiments, and observational causal methods (e.g., diff-in-diff, synthetic control, propensity score methods).
  • - Develop scalable analytical pipelines for impact measurement, KPI development, metric integrity validation, and long-term business monitoring.
  • - Apply NLP and statistical modeling techniques-including topic modeling, clustering, semantic similarity, and classification-to uncover insights from unstructured seller interactions, feedback, and content.
  • - Partner with scientists, engineers, economists, and product managers to translate ambiguous problems into structured analytical approaches and influence product roadmaps with data-driven recommendations.
  • - Build and maintain automated analytics tools and dashboards to democratize insights for product, science, and engineering teams.
  • - Collaborate scientists to evaluate model-driven features, quantify impact, and ensure mechanisms are grounded in rigorous measurement.
  • - Research and experiment with new analytical and measurement methodologies, ensuring Amazon leverages the latest best practices in causal inference, NLP, and GenAI.
View full posting on CareerOneStop → ID: 0bf2d38bf5af
Data Scientist, SPX AI Lab, SPX Science
Amazon · Seattle, WA
Mid-level Master's
2026-04-25
Requirements
  • 2+ years of data scientist experience
  • 3+ years of data querying languages (e.g. SQL), scripting languages (e.g. Python) or statistical/mathematical software (e.g. R, SAS, Matlab, etc.) experience
  • 3+ years of machine learning/statistical modeling data analysis tools and techniques, and parameters that affect their performance experience
  • 1+ years of working with or evaluating AI systems experience
  • Master's degree in Science, Technology, Engineering, or Mathematics (STEM), or experience working in Science, Technology, Engineering, or Mathematics (STEM)
Preferred
  • Knowledge of machine learning concepts and their application to reasoning and problem-solving
  • Experience in a ML or data scientist role with a large technology company
  • Experience in defining and creating benchmarks for assessing GenAI model performance
  • Experience working on multi-team, cross-disciplinary projects
  • Experience applying quantitative analysis to solve business problems and making data-driven business decisions
  • Experience effectively communicating complex concepts through written and verbal communication
Responsibilities
  • - Respond to Seller feedback and implement fix in Gen AI solution to enhance Seller experience
  • - Drive deep-dive analytical studies to understand seller pain points, evaluate feature performance, and identify opportunities to improve the Selling Partner experience.
  • - Design and execute robust causal inference and measurement frameworks, including A/B testing, quasi-experiments, and observational causal methods (e.g., diff-in-diff, synthetic control, propensity score methods).
  • - Develop scalable analytical pipelines for impact measurement, KPI development, metric integrity validation, and long-term business monitoring.
  • - Apply NLP and statistical modeling techniques-including topic modeling, clustering, semantic similarity, and classification-to uncover insights from unstructured seller interactions, feedback, and content.
  • - Partner with scientists, engineers, economists, and product managers to translate ambiguous problems into structured analytical approaches and influence product roadmaps with data-driven recommendations.
  • - Build and maintain automated analytics tools and dashboards to democratize insights for product, science, and engineering teams.
  • - Collaborate scientists to evaluate model-driven features, quantify impact, and ensure mechanisms are grounded in rigorous measurement.
  • - Research and experiment with new analytical and measurement methodologies, ensuring Amazon leverages the latest best practices in causal inference, NLP, and GenAI.
View full posting on CareerOneStop → ID: 6c6c5b5d3d9b
Master's Fall Machine Learning Internship (ATG - Visual Search)
Pinterest, Inc. · Seattle, WA
Intern Master's
2026-04-24
Requirements
  • This role will be on our Visual Search team. We are looking for candidates with experience in Computer Vision, Visual Search, User Understanding, Generative AI, and LLMs.
  • Ability to legally work full time (40 hours/week) from September-December 2026
  • Working towards a Master's degree in Computer Science, ML, NLP, Statistics, Informati
Responsibilities
  • Develop and launch new user features using unique internal datasets and ML techniques, especially in computer vision, generative AI, and responsible AI.
  • Gain hands-on experience with production ML systems, including algorithmic research, infrastructure, data engineering, training, inference, and product, to deliver innovative solutions. You will be exposed to full-stack production ML systems.
  • Leverage frontier AI tools and agents to accelerate engineering implementation, including prototyping and experimentation work.
  • Validate AI-generated outputs through testing, code review, and critical thinking, ensuring solutions are accurate, maintainable, secure, and aligned with team standards.
  • Use AI to better understand unfamiliar code, investigate bugs, and summarize technical context or documentation.
  • Contribute in cutting-edge research in machine learning and artificial intelligence that can be applied to Pinterest problems
  • Write clean, efficient, and sustainable code
  • Take proactive ownership over the completion and quality of your tasks and project with minimal guidance from your mentor, manager, and peers
View full posting on CareerOneStop → ID: 52fd99247f6f
Machine Learning Engineer
Indeed · Seattle, WA
Mid-level Master's
2026-04-23
Responsibilities
  • The Machine Learning Engineer I role partners closely with business partners across various functions to help execute strategic initiatives that increase revenue, drive operational scale, and improve efficiency for continuous growth. As a Machine Learning Engineer, you will prepare datasets, train and optimize models, and maintain and improve model inference services. You will learn and apply new techniques from open source packages and research publications, and creatively adapt models for solving business problems across Indeed.
  • Work spans classical ML through LLM systems. You improve search and retrieval quality using real user signals. Execution includes experiments, iteration, and production reliability at scale. You collaborate with engineers, data scientists, and product teams to define problems, test approaches, and ship measurable improvements.
  • Build AI/ML systems for search, ranking, and recommendations
  • Develop LLM retrieval and generation workflows
  • Improve search and ranking relevance
  • Design metrics and run experiments
  • Monitor model quality, latency, and cost
  • Debug data, models, and system issues
  • Build training, inference, and eval pipelines
  • *Skills/Competencies
  • Requires a Bachelor's degree in Computer Science, Mathematics, or Statistics, and a minimum of 2 years of related experience; or an advanced degree without experience
  • Experience building ML models in Python; solid software engineering and algorithms fundamentals
  • Experience developing backend services in Java/Kotlin for ML-driven systems and features
  • Experience writing clean, testable, and maintainable production code
  • Experience working with structured and unstructured data, including SQL for large-scale data querying, and building scalable data pipelines and features from data
  • Experience integrating ML models into search systems using engines such as OpenSearch or similar, with familiarity in container orchestration for deployment with senior guidance
  • Excellent understanding of model evaluation techniques, feature engineering, experiment design, and familiarity with LLM systems (RAG, embeddings, output evaluation)
View full posting on CareerOneStop → ID: 8e3fc20531d1
Machine Learning Engineer
Indeed · Portland, OR
Mid-level Master's
2026-04-23
Responsibilities
  • The Machine Learning Engineer I role partners closely with business partners across various functions to help execute strategic initiatives that increase revenue, drive operational scale, and improve efficiency for continuous growth. As a Machine Learning Engineer, you will prepare datasets, train and optimize models, and maintain and improve model inference services. You will learn and apply new techniques from open source packages and research publications, and creatively adapt models for solving business problems across Indeed.
  • Work spans classical ML through LLM systems. You improve search and retrieval quality using real user signals. Execution includes experiments, iteration, and production reliability at scale. You collaborate with engineers, data scientists, and product teams to define problems, test approaches, and ship measurable improvements.
  • Build AI/ML systems for search, ranking, and recommendations
  • Develop LLM retrieval and generation workflows
  • Improve search and ranking relevance
  • Design metrics and run experiments
  • Monitor model quality, latency, and cost
  • Debug data, models, and system issues
  • Build training, inference, and eval pipelines
  • *Skills/Competencies
  • Requires a Bachelor's degree in Computer Science, Mathematics, or Statistics, and a minimum of 2 years of related experience; or an advanced degree without experience
  • Experience building ML models in Python; solid software engineering and algorithms fundamentals
  • Experience developing backend services in Java/Kotlin for ML-driven systems and features
  • Experience writing clean, testable, and maintainable production code
  • Experience working with structured and unstructured data, including SQL for large-scale data querying, and building scalable data pipelines and features from data
  • Experience integrating ML models into search systems using engines such as OpenSearch or similar, with familiarity in container orchestration for deployment with senior guidance
  • Excellent understanding of model evaluation techniques, feature engineering, experiment design, and familiarity with LLM systems (RAG, embeddings, output evaluation)
View full posting on CareerOneStop → ID: 798a789e964a
Data Scientist III - AMZ9971313
Amazon · Seattle, WA
Mid-level Master's
2026-04-22
Preferred
  • Please see job description and the position requirements above.
Responsibilities
  • Own the data science elements of various products to help with data-based decision making, product performance optimization, and product performance tracking. Work directly with product managers to help drive the design of the product. Work with Technical Product Managers to help drive the build planning. Translate business problems and products into data requirements and metrics. Initiate the design, development, and implementation of scientific analysis projects or deliverables. Own the analysis, modelling, system design, and development of data science solutions for products. Write documents and make presentations that explain model/analysis results to the business. Bridge the degree of uncertainty in both problem definition and data scientific solution approaches. Build consensus on data, metrics, and analysis to drive business and system strategy.
  • 40 hours / week, 8:00am-5:00pm, Salary Range $165,006/year to $215,300/year.
  • Amazon is a total compensation company. Dependent on the position offered, equity, sign-on payments, and other forms of compensation may be provided as part of a total compensation package, in addition to a full range of medical, financial, and/or other benefits. For more information, visit:
View full posting on CareerOneStop → ID: fcdf242c6404
ML Engineer - Automated Evaluation and Adversarial Design
Apple · Seattle, WA
Mid-level Master's
2026-04-22
Requirements
  • Bachelor's degree in Computer Science, Machine Learning, Statistics, or a related field
  • 4+ years of experience building or significantly extending ML evaluation systems, including designing evaluation benchmarks or quality assessment frameworks including evaluation of sequential or multi-step AI outputs
  • Experience independently defining evaluation architecture and methodology for AI or ML systems with the ability to design evaluation approaches where the unit of analysis is a conversation or session rather than a single output
  • Experience designing adversarial or red-teaming test methodologies for ML models or AI-powered features including adversarial scenarios that target failures across multi-turn interactions
  • Experience with Python and ML frameworks (PyTorch, TensorFlow, or equivalent) in production or near-production settings
  • Track record of owning technical direction for evaluation efforts across multiple features or product areas
Preferred
  • Experience evaluating user-facing AI features in consumer applications, with an understanding of how technical metrics connect to user-perceived quality
  • Familiarity with productivity software or creative tools, with the ability to assess output quality from a user workflow perspective
  • Experience ensuring alignment between automated and human evaluation methods, including inter-annotator agreement analysis and bias detection
  • Track record of designing evaluation systems that scale across multiple features or product areas without requiring bespoke solutions for each
  • Experience evaluating different types of AI systems, including API-based and custom-trained models
  • Demonstrated ability to communicate evaluation findings and readiness assessments to cross-functional partners
  • Experience leveraging automation to scale evaluation data generation and analysis
  • Experience building evaluation pipelines for conversational AI, dialogue systems, or agentic workflows, including turn-level and session-level automated scoring
  • Familiarity with agent orchestration frameworks (LangChain, LangGraph, CrewAI, AutoGen) and observability tooling (LangSmith, Braintrust, Arize), with an understanding of how to instrument and evaluate multi-step agent runs
  • Experience designing adversarial tests for tool-use reliability, function-calling accuracy, or agent planning quality
  • Graduate degree in a relevant field
Responsibilities
  • The Productivity and Machine Learning Evaluation team ensures the quality of AI-powered features across a suite of productivity and creative applications; including Creator Studio, used by hundreds of millions of people. This team serves as the primary evaluation function, providing critical quality signals that directly influence model development decisions and product launches.
  • This role focuses on building and scaling automated evaluation systems and designing adversarial and stress-testing methodologies across multiple AI features. The work requires a deep understanding of how AI systems fail and how to measure quality rigorously. As features evolve from single-turn interactions into multi-turn, agentic experiences, the evaluation challenge shifts from assessing individual outputs to stress-testing entire conversation flows and agent decision chains. This is an opportunity to shape the evaluation infrastructure that determines whether AI features meet the bar for hundreds of millions of users.
  • Day-to-day work involves designing, building, and maintaining automated evaluation systems that assess AI feature quality at scale, including multi-turn conversation evaluation and end-to-end agent workflow testing. This includes creating adversarial test suites that probe model weaknesses and running stress tests to ensure features perform under demanding conditions, with particular focus on failure modes that only emerge across extended interactions, such as: context degradation, goal drift, and compounding errors.
  • Typical deliverables include: evaluation frameworks and rubrics, quality assessment reports, adversarial test case libraries, multi-turn stress-test pipelines, and recommendations on model readiness.
View full posting on CareerOneStop → ID: 3c394469498c
ML Engineer - Evaluation Analysis, Metric and Data Strategy
Apple · Seattle, WA
Mid-level Master's
2026-04-22
Requirements
  • Bachelor's degree in Statistics, Data Science, Applied Mathematics, Computer Science, or a related quantitative field
  • 5+ years of experience in applied science, data science, or evaluation research, with a focus on defining and operationalizing quality metrics
  • Experience with statistical analysis methods including significance testing, sampling design, effect size estimation, and experimental design
  • Experience working with production user data, understanding its biases and limitations compared to controlled evaluation data, including familiarity with sequential interaction data where context and turn order affect quality assessment
  • Ability to design evaluation approaches where the unit of analysis is a session or conversation rather than a single model output
  • Track record of independently designing metrics frameworks and driving data-informed decisions across cross-functional teams
  • Proficiency in Python (pandas, scipy, scikit-learn) or R for data analysis and visualization
Preferred
  • Experience designing evaluation or quality metrics for AI-powered or ML-driven features in consumer-facing products
  • Familiarity with productivity software or creative applications, with an ability to distinguish between technically correct and genuinely useful AI outputs
  • Experience partnering with engineering or data teams to define data collection requirements and schemas
  • Track record of translating complex analytical findings into concise recommendations for non-technical decision-makers
  • Experience evaluating tool-use accuracy, retrieval quality, or function-calling reliability within AI systems
  • Experience with evaluation methodology including inter-annotator agreement, evaluation bias detection, and dataset representativeness auditing
  • Familiarity with agentic orchestration frameworks (LangChain, LangGraph, CrewAI, AutoGen) and emerging agent interoperability protocols (A2A, MCP), with an understanding of how architectural choices in agent design affect evaluability
  • Understanding of ML model development processes, with the ability to specify what evaluation signals are useful for model improvement
  • Experience managing evaluation across multiple features or product areas simultaneously, with systematic rather than ad-hoc approaches
  • Graduate degree in a relevant quantitative field
Responsibilities
  • The Productivity and Machine Learning Evaluation team ensures the quality of AI-powered features across a suite of productivity and creative applications; including Creator Studio, used by hundreds of millions of people. This team serves as the primary evaluation function, and its analysis directly informs decisions about model development, feature launches, and product direction.
  • This role is the analytical core of the team; responsible for making sense of evaluation signals and real-world user behavior. The work involves designing feature-level quality metrics, collaborating with partner teams on data collection strategies, and translating evaluation data into concise, actionable insights that drive decisions. This is an opportunity to define how AI feature quality is measured and to directly shape what gets shipped. As AI features evolve into multi-turn, agentic experiences, this role will define what "quality" means when the unit of evaluation is a conversation, not a single response.
  • Day-to-day work involves analyzing evaluation results, identifying trends, regressions, and segment-level patterns across multiple AI features. This includes collaborating with partner teams on data collection strategies, ensuring evaluation data is representative of real-world usage, and designing the metrics framework that leadership uses to make decisions on AI features.
  • Typical deliverables include: feature-level quality metrics and dashboards, evaluation analysis reports, data collection requirements, dataset representativeness audits, multi-turn evaluation frameworks and session-level scoring rubrics, and concise metric summaries for decision-makers.
View full posting on CareerOneStop → ID: bb191e99c6a9
Generative AI Senior Data Scientist
Norstella · Olympia, WA
Senior Master's
2026-04-22
Requirements
  • Degree at Masters level or higher in a STEM field such as Math, Physics, Computer Science, Engineering, or equivalent practical experience
  • Excellent knowledge of python and core data science libraries, and using LLM libraries as part of algorithm design
  • Project lead experience, managing stakeholders and highly specialized professionals in other non-technical
  • Excellent technical communication skills when working with a broader development and product team
  • Knowledge of Scrum, Kanban, and other Agile methodologies, as well as breaking down tasks into Jira tickets
Preferred
  • Experience with AWS, serverless compute, containerization and storage
  • Knowledge of the pharmaceutical industry, in particular the stages of pharmaceutical product development and clinical language / ontologies
  • Ability to rapidly prototype new product ideas with a basic familiarity across the full stack, webapp to database
  • Experience using external APIs in a production context
Responsibilities
  • In this role as a Generative AI Senior Data Scientist you will:
  • Work with our Product leadership within Norstella to define and shape new offerings where agents and assistants can help customers
  • Manage a team of data scientists and developers to provide Generative AI-enabled API services to the front end dev team
  • Manage a roadmap of Generative AI work, mixing new product development and enhancements to existing services
  • Define LLM and Agent architectures suitable to answer complex questions, including via code interpreting, LLM tool use and leveraging secondary data science models
  • Coach and train a team of data scientists and developers to use these architectures
  • Stay up-to-date, constantly learning about advances in the field, and deliver periodic presentations to the data science team on these developments
  • All other duties, as assigned
  • *How You'll Succeed
  • Ultimately our goal is to smooth patient access to life-saving therapies. You will work with R&D pharma specialists to understand a problem which is hindering developing and releasing effective new pharma products which we believe we can help with. After understanding the problem you will conceptualize potential solutions; this will involve breaking down the problem into individual steps, identifying how our existing framework of services can fit in, and what modifications and extensions are necessary for a successful launch. Finally, an overall solution can be packaged together, mixed with classical logic and business rules. As a Senior-level engineer you will be primarily responsible for one major release at a time.
  • After conceiving potential solution(s), you will research potential packages, LLMs, and approaches, document the high-level tasks in Jira with estimates for time taken for yourself and other data scientists and python developers to implement the solution as a proof-of-concept. You will deliver indicative results starting from test questions into answer datasets for exploration by the broader multi-functional team. You will also perform code reviews with the data science team to examine their implementation and consider ways of strengthening the final codebase and methodology.
  • After iterating the design with the multi-functional team as part of customer-led product development, you might convert your prototype into a full product. This will involve productionizing code from you and the team to a high standard, containerization, and deployment of the algorithm, usually in AWS ECS, using existing CICD templates. Over time you may revisit this product, re-evaluate its performance, and redesign/improve as required. Historically, if successful, a General Availability launch is typically ~6 months from project start.
View full posting on CareerOneStop → ID: 7b1d2ac94fe7
Senior Data Scientist
Norstella · Olympia, WA
Senior Master's
2026-04-22
Requirements
  • 5+ years of experience developing AI / ML applications and data driven solutions, preferably in regulated industries (pharma, legal, financial services, or energy)
  • Graduate degree in Computer Science, Engineering, Statistics or a related quantitative discipline, or equivalent work experience
  • Substantial depth and breadth in NLP, Deep Learning, Generative AI, LLMs, and other state of the art AI / ML techniques
  • Deep experience with LLM orchestration frameworks such as LangChain, LlamaIndex, or similar libraries
  • Expert-level knowledge of LLM APIs (OpenAI, Anthropic Claude) and open-source models (Llama, Mistral)
  • Deep understanding of CS fundamentals, computational complexity and algorithm design
  • Experience with building large-scale distributed systems in an agile environment and the ability to build quick prototypes
  • Excellent knowledge of Python and core data science and AI libraries including Pandas, NumPy, PyTorch, and simila
  • Experience building or utilizing Model Context Protocol (MCP) servers to bridge models with data tools
  • Strong background in scalable backend environments (Docker, Kubernetes, AWS/GCP)
  • Experience moving AI from prototype to production-grade services with monitoring, logging, and rate-limiting
  • Ability to independently conduct research and develop appropriate algorithmic solutions to complex business problems
  • Experience mentoring junior team members
  • Excellent problem solving and communication skills
Preferred
  • Knowledge of the healthcare / pharma domain and experience with applying AI to healthcare data
  • Experience with AWS, especially ECS, Bedrock, API Gateway, SageMaker, serverless compute and storage such as S3 and Snowflake
  • Proficiency with vector databases such as Pinecone, Qdrant, or similar for high-performance retrieval
  • Experience with RAG patterns, prompt engineering, model fine tuning, and knowledge graphs
  • Experience with unstructured document processing (legal document analysis, contract management, data retrieval)
  • Experience with Big Data tools like Apache Spark, Hadoop, or Databricks
Responsibilities
  • Our dedicated Data Science team is at the forefront of revolutionizing pharma intelligence and how patients gain access to life-saving therapies. Armed with cutting-edge technology and a passion for innovation, we leverage the vast landscape of data to extract actionable insights that drive informed decision making.
  • Our unique collaborative approach fosters a dynamic synergy between data science and product development. Our deep expertise in machine learning, artificial intelligence, large language models, and generative AI, combined with our domain knowledge, enables us to deliver comprehensive, production-grade AI solutions that empower our clients to stay ahead in a rapidly evolving industry.
  • In this role as a Senior Data Scientist, you will:
  • Design and deploy production-ready AI systems that leverage LLMs and advanced ML techniques to solve complex business problems across pharma intelligence
  • Build and maintain multi-agent systems and agentic orchestration workflows using frameworks like LangChain, LangGraph, or AutoGen to execute autonomous tasks
  • Develop and optimize Retrieval-Augmented Generation (RAG) pipelines, ensuring high-fidelity context retrieval and vector database management
  • Implement and extend MCP (Model Context Protocol) servers to allow LLMs to interact safely and efficiently with local and remote data sources
  • Architect robust, scalable APIs and microservices to serve AI features to end-users with low latency (FastAPI or similar)
  • Collaborate with product partners and other scientists to identify new opportunities to apply AI / ML to our content and products
  • Conduct research and identify AI / ML algorithms and methods to solve specific business problems, and deliver these algorithms as microservices in collaboration with content and product engineering teams
  • Implement rigorous testing and evaluation frameworks for LLM outputs to ensure prompt stability, prevent regressions, and manage hallucination risks
  • Contribute towards the common data science platform
  • Stay up-to-date, constantly learning about advances in the field, and deliver periodic presentations to internal teams on these developments
  • All other duties, as assigned
View full posting on CareerOneStop → ID: f86e2dffa9ab
Data Scientist II, Amazon Stores Finance Science
Amazon · Bellevue, WA
Mid-level Master's
2026-04-21
Requirements
  • 2+ years of data scientist experience
  • 3+ years of data querying languages (e.g. SQL), scripting languages (e.g. Python) or statistical/mathematical software (e.g. R, SAS, Matlab, etc.) experience
  • 3+ years of machine learning/statistical modeling data analysis tools and techniques, and parameters that affect their performance experience
  • Experience applying theoretical models in an applied environment
  • Bachelor's degree
Preferred
  • Experience in a ML or data scientist role with a large technology company
  • Experience working on multi-team, cross-disciplinary projects
  • Experience effectively communicating complex concepts through written and verbal communication
  • Master's degree
  • Experience formulating and solving predictive modeling, machine learning, forecasting or statistical modeling problems
Responsibilities
  • Demonstrating thorough technical knowledge, effective exploratory data analysis, and model building using industry standard ML models
  • Working with technical and non-technical stakeholders across every step of science project life cycle
  • Collaborating with finance, product, data engineering, and software engineering teams to create production implementations for large-scale ML models
  • Innovating by adapting new modeling techniques and procedures
  • Presenting research results to our internal research community
View full posting on CareerOneStop → ID: 1e66715e63dc
Staff Product Data Scientist, Ads Privacy and Safety
Google · Kirkland, WA
Senior Master's
2026-04-18
Requirements
  • Bachelor's degree in Statistics, Mathematics, Data Science, Engineering, Physics, Economics, or a related quantitative field.
  • 10 years of experience using analytics to solve product or business problems, performing statistical analysis, and coding (e.g., Python, R, SQL) or 8 years of experience with a Master's degree.
Preferred
  • Master's degree in Statistics, Mathematics, Data Science, Engineering, Physics, Economics, or a related quantitative field.
  • Familiarity with global privacy regulations (e.g., General Data Protection Regulation (GDPR), California Consumer Privacy Act (CCPA), Digital Markets Act (DMA)) and their implications relevant to technology companies.
  • Knowledge of financial forecasting, scenario analysis and risk assessment for Ads.
Responsibilities
  • The Ads Privacy and Safety team (APaS) is dedicated to fostering trust and transparency within the Google Ads ecosystem. This involves ensuring safety and respect for users, advertisers, and publishers by combating invalid traffic, promoting privacy-respecting business generation practices that empower user control, and advancing content understanding through human and machine intelligence.
  • The APaS Data Science team plays a crucial role in safeguarding the integrity of Google's advertising platform. By focusing on data-driven objectivity, accountability, and user-centricity, this team develops unbiased frameworks to measure business health and deliver impact assessments across key areas like risk, business, and user trust. They proactively counter threats by enabling precise measurement and ensuring the focus remains on the right problems. Through close partnerships across APaS, the team provides continuous measurement and influences strategic decisions with objective insights.
  • As a Senior Data Scientist, you will join our Ads privacy and regulations team. In this crucial role, you will drive data-driven decision-making to ensure regulatory compliance and unlock growth opportunities within Google Ads, safeguarding billions in business while enhancing user trust. You will be a key player in navigating the complex landscape of privacy laws and regulations, developing quantitative models and frameworks that enable Google Ads to adapt and grow. You will be responsible for analyzing the impact of evolving regulations, quantifying risks and opportunities, and generating actionable insights that inform product development, policy adjustments, and using user preference and consented signals effectively for Ads targeting.The US base salary range for this full-time position is $192,000-$278,000 + bonus + equity + benefits. Our salary ranges are determined by role, level, and location. Within the range, individual pay is determined by work location and additional factors, including job-related skills, experience, and relevant education or training. Your recruiter can share more about the specific salary range for your preferred location during the hiring process.
  • Please note that the compensation details listed in US role postings reflect the base salary only, and do not include bonus, equity, or benefits. Learn more aboutbenefits at Google (https://careers.google.com/benefits/) .
  • Partner with cross-functional teams and deliver data driven insights to stakeholders across Ads, focusing on advertiser, publisher, and user trust and experience.
  • Develop and implement quantitative frameworks to assess the impact of Ads safety, traffic quality, user privacy and regulatory compliance on Ads business, user experience, and product capabilities.
  • Identify areas for optimization in response to evolving trends in the Ads industry and develop models to improve product features against business impact and new threats.
  • Build and automate reports, iteratively build and prototype dashboards to provide insights at scale, solving for investigative need.
  • Deliver effective presentations of findings and recommendations to multiple levels of leadership, creating visual displays of quantitative information.
  • Information collected and processed as part of your Google Careers profile, and any job applications you choose to submit is subject to Google'sApplicant and Candidate Privacy Policy (./privacy-policy) .
View full posting on CareerOneStop → ID: 0ee7a56a7c38
Machine Learning Engineer
Indeed · Portland, OR
Mid-level Master's
2026-04-16
Responsibilities
  • The Machine Learning Engineer I role partners closely with business partners across various functions to help execute strategic initiatives that increase revenue, drive operational scale, and improve efficiency for continuous growth. As a Machine Learning Engineer, you will prepare datasets, train and optimize models, and maintain and improve model inference services. You will learn and apply new techniques from open source packages and research publications, and creatively adapt models for solving business problems across Indeed.
  • Work spans classical ML through LLM systems. You improve search and retrieval quality using real user signals. Execution includes experiments, iteration, and production reliability at scale. You collaborate with engineers, data scientists, and product teams to define problems, test approaches, and ship measurable improvements.
  • Build AI/ML systems for search, ranking, and recommendations
  • Develop LLM retrieval and generation workflows
  • Improve search and ranking relevance
  • Design metrics and run experiments
  • Monitor model quality, latency, and cost
  • Debug data, models, and system issues
  • Build training, inference, and eval pipelines
  • *Skills/Competencies
  • Requires a Bachelor's degree in Computer Science, Mathematics, or Statistics, and a minimum of 2 years of related experience; or an advanced degree without experience
  • Experience building ML models in Python; solid software engineering and algorithms fundamentals
  • Experience developing backend services in Java/Kotlin for ML-driven systems and features
  • Experience writing clean, testable, and maintainable production code
  • Experience working with structured and unstructured data, including SQL for large-scale data querying, and building scalable data pipelines and features from data
  • Experience integrating ML models into search systems using engines such as OpenSearch or similar, with familiarity in container orchestration for deployment with senior guidance
  • Excellent understanding of model evaluation techniques, feature engineering, experiment design, and familiarity with LLM systems (RAG, embeddings, output evaluation)
View full posting on CareerOneStop → ID: d701d3f0cddb
Senior Data Scientist, Product, Ads Privacy and Safety
Google · Kirkland, WA
Senior Master's
2026-04-15
Requirements
  • Bachelor's degree in Statistics, Mathematics, Data Science, Engineering, Physics, Economics, or a related quantitative field.
  • 8 years of experience using analytics to solve product or business problems, performing statistical analysis, and coding (e.g., Python, R, SQL) or 5 years of experience with a Master's degree.
Preferred
  • Master's degree in Statistics, Mathematics, Data Science, Engineering, Physics, Economics, or a related quantitative field.
  • Familiarity with global privacy regulations (e.g., General Data Protection Regulation (GDPR), California Consumer Privacy Act (CCPA), Digital Markets Act (DMA)) and their implications relevant to technology companies.
  • Knowledge of financial forecasting, scenario analysis and risk assessment for Ads.
Responsibilities
  • The Ads Privacy and Safety team (APaS) is dedicated to fostering trust and transparency within the Google Ads ecosystem. This involves ensuring safety and respect for users, advertisers, and publishers by combating invalid traffic, promoting privacy-respecting business generation practices that empower user control, and advancing content understanding through human and machine intelligence.
  • The APaS Data Science team plays a crucial role in safeguarding the integrity of Google's advertising platform. By focusing on data-driven objectivity, accountability, and user-centricity, this team develops unbiased frameworks to measure business health and deliver impact assessments across key areas like risk, business, and user trust. They proactively counter threats by enabling precise measurement and ensuring the focus remains on the right problems. Through close partnerships across APaS, the team provides continuous measurement and influences strategic decisions with objective insights.
  • As a Senior Data Scientist, you will join our Ads privacy and regulations team. In this crucial role, you will drive data-driven decision-making to ensure regulatory compliance and unlock growth opportunities within Google Ads, safeguarding billions in business while enhancing user trust. You will be a key player in navigating the complex landscape of privacy laws and regulations, developing quantitative models and frameworks that enable Google Ads to adapt and grow. You will be responsible for analyzing the impact of evolving regulations, quantifying risks and opportunities, and generating actionable insights that inform product development, policy adjustments, and using user preference and consented signals effectively for Ads targeting.
  • The US base salary range for this full-time position is $163,000-$237,000 + bonus + equity + benefits. Our salary ranges are determined by role, level, and location. Within the range, individual pay is determined by work location and additional factors, including job-related skills, experience, and relevant education or training. Your recruiter can share more about the specific salary range for your preferred location during the hiring process.
  • Please note that the compensation details listed in US role postings reflect the base salary only, and do not include bonus, equity, or benefits. Learn more aboutbenefits at Google (https://careers.google.com/benefits/) .
  • Partner with cross-functional teams and deliver data driven insights to stakeholders across Ads, focusing on advertiser, publisher, and user trust and experience.
  • Develop and implement quantitative frameworks to assess the impact of Ads safety, traffic quality, user privacy and regulatory compliance on Ads business, user experience, and product capabilities.
  • Identify areas for optimization in response to evolving trends in the Ads industry and develop models to improve product features against business impact and new threats.
  • Build and automate reports, iteratively build and prototype dashboards to provide insights at scale, solving for analytical need.
  • Deliver effective presentations of findings and recommendations to multiple levels of leadership, creating visual displays of quantitative information.
  • Information collected and processed as part of your Google Careers profile, and any job applications you choose to submit is subject to Google'sApplicant and Candidate Privacy Policy (./privacy-policy) .
View full posting on CareerOneStop → ID: f1f3b5414ab0
Senior Data Scientist, Amazon Stores Finance Science, Amazon Stores Finance Science
Amazon · Bellevue, WA
Senior Master's
2026-04-05
Requirements
  • 5+ years of data querying languages (e.g. SQL), scripting languages (e.g. Python) or statistical/mathematical software (e.g. R, SAS, Matlab, etc.) experience
  • 4+ years of data scientist experience
  • Experience with statistical models e.g. multinomial logistic regression
  • Bachelor's degree in a quantitative field such as statistics, mathematics, data science, business analytics, economics, finance, engineering, or computer science
  • Experience managing data pipelines
Preferred
  • Experience as a leader and mentor on a data science team
  • Knowledge of AWS tech stack (e.g., AWS Redshift, S3, EC2, Glue)
  • Master's degree
  • Experience formulating and solving predictive modeling, machine learning, forecasting or statistical modeling problems
Responsibilities
  • Demonstrating thorough technical knowledge, effective exploratory data analysis, and model building using industry standard ML models
  • Working with technical and non-technical stakeholders across every step of science project life cycle
  • Collaborating with finance, product, data engineering, and software engineering teams to create production implementations for large-scale ML models
  • Innovating by adapting new modeling techniques and procedures
  • Presenting research results to our internal research community
View full posting on CareerOneStop → ID: d73d393e6308
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