Job Matches
Washington job postings for occupations your coursework prepares you for. Sorted by how many of the occupation's tasks your courses cover.
Demo profile: Math BS with Data Science minor. Sign in (GitHub) to rank these jobs against your own courses, projects, internships, and work experience — each added signal sharpens the qualification match.
50 Washington postings
across 1 occupation the EWU Math BS prepares you for
· ranked by how many tasks your 16 declared courses cover.
Showing CareerOneStop postings from the last 30 days; the scraper re-syncs from CareerOneStop nightly. Last posting in this list dated 2026-06-05.
Scraper last re-confirmed a WA posting 2026-06-05 07:57 (183 touched today).
Showing CareerOneStop postings from the last 30 days; the scraper re-syncs from CareerOneStop nightly. Last posting in this list dated 2026-06-05.
Scraper last re-confirmed a WA posting 2026-06-05 07:57 (183 touched today).
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tasks
Machine Learning Engineer - News, Books, and Stocks Team
Apple
Seattle, WA
2026-06-04
Role Number: 200660323-3337 Summary In a time where the news and book media landscapes are changing by the day, Apple News and Apple Books stand as champions of quality content, expert curation, user privacy, and the judicious use of machine learning. Our lively and brilliant team cons
Requirements
- MS in Machine Learning, Computer Science, or related field. Alternatively, equivalent industry experience to an MS degree is acceptable.
- At least 2 years of experience shipping machine learning models in products.
- Strong programming skills in Python, Java, or a related language, and one of the deep learning toolkits such as PyTorch, TensorFlow, or similar.
- Ability to communicate effectively and collaborate with partner teams.
What you'd do
- In a time where the news and book media landscapes are changing by the day, Apple News and Apple Books stand as champions of quality content, expert curation, user privacy, and the judicious use of ma… In a time where the news and book media landscapes are changing by the day, Apple News and Apple Books stand as champions of quality content, expert curation, user privacy, and the judicious use of machine learning. Our lively and brilliant team consists of client and machine learning engineers who embody Apple's values. We inspire, teach, and otherwise enable each other to do the best work of our careers. Our team's outstanding retention rate speaks to our strong culture of respect for our teammates as both engineers and people. Would you like to work on such a team, solving hard problems in machine learning? Terrific! Please join us for the next generation of these apps!
- Our team is seeking a high-energy and self-driven machine learning engineer who will play a central role in the delivery of scalable services. The team uses machine learning to tackle difficult and co… Our team is seeking a high-energy and self-driven machine learning engineer who will play a central role in the delivery of scalable services. The team uses machine learning to tackle difficult and complicated problems in the news, books, and stocks domains, including text extraction, named entity recognition, duplicate detection, search, ranking, and much more! As a member of our dynamic group, you'll have the rare and rewarding opportunity to craft upcoming products that will delight and encourage millions of Apple's customers every day!
Nice to have
- Ph.D. in Machine Learning, Computer Science, or related field.
- At least 5 years of experience shipping machine learning models in products.
- Experience with recommender systems.
- Experience with text-centric AI/ML (LLMs, document classification, search, etc.)
Tasks you're prepared for
(15 of 16 for Data Scientists)
- Analyze, manipulate, or process large sets of data using statistical software.
-
Apply feature selection algorithms to models predicting outcomes of interest, such as sales, attrition, and healthcare use.
via CSCD 484
- Apply sampling techniques to determine groups to be surveyed or use complete enumeration methods.
- Clean and manipulate raw data using statistical software.
- Compare models using statistical performance metrics, such as loss functions or proportion of explained variance.
+10 more covered tasks
Tasks you'd need to develop
(1)
Recommend data-driven solutions to key stakeholders.
These could be filled by an applied project, elective, or internship — see the program page for examples.
15/16
tasks
Data Scientist I, Demand Forecasting
Amazon
Bellevue, WA
2026-06-04
Description Amazon has the world's most complex supply chain: we fulfill global demand for hundreds of millions of products at lightning fast delivery speeds. We need your skills to optimize our supply chain, with the end goal of delighting our customers. A core part of the supply chain operations
Requirements
- 3+ years of data querying languages (e.g. SQL), scripting languages (e.g. Python) or statistical/mathematical software (e.g. R, SAS, Matlab, etc.) experience
- 3+ years of data/research scientist, statistician or quantitative analyst in an internet-based company with complex and big data sources experience
- Bachelor's degree
- Familiarity with large language models (LLMs) or generative AI applications in analytics or explainability
What you'd do
- Design and analyze experiments (A/B tests) to measure the impact of forecast model changes and SCOT initiatives, drawing causal inferences from both experimental and observational data
- Develop bias correction models to improve forecast accuracy across Amazon's demand forecasting systems, including National, Regional, Grocery, SSD, Inbound, and CIV forecasts
- Contribute to GenAI/LLM-based research for forecast explainability and interpretability, helping stakeholders understand what drives forecast signals
- Support and enhance the Labs experimentation platform by building scalable inference and measurement solutions that quantify the impact of forecasting improvements
Nice to have
- Knowledge of statistical packages and business intelligence tools such as SPSS, SAS, S-PLUS, or R
- Experience with clustered data processing (e.g., Hadoop, Spark, Map-reduce, and Hive)
- Experience with time series forecasting, demand modeling, or bias correction techniques
Tasks you're prepared for
(15 of 16 for Data Scientists)
- Analyze, manipulate, or process large sets of data using statistical software.
-
Apply feature selection algorithms to models predicting outcomes of interest, such as sales, attrition, and healthcare use.
via CSCD 484
- Apply sampling techniques to determine groups to be surveyed or use complete enumeration methods.
- Clean and manipulate raw data using statistical software.
- Compare models using statistical performance metrics, such as loss functions or proportion of explained variance.
+10 more covered tasks
Tasks you'd need to develop
(1)
Recommend data-driven solutions to key stakeholders.
These could be filled by an applied project, elective, or internship — see the program page for examples.
15/16
tasks
Data Scientist - Pricing
Microsoft Corporation
Redmond, WA
2026-06-04
Overview The Cloud and AI Platforms Monetization organization is a big picture team that encourages a diverse and inclusive culture. We are growth strategists who enable the Microsoft mission by creating durable profit growth through high-impact monetization strategies, packaging, and pricing.
Requirements
- Doctorate in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field
- OR Master's Degree in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field AND 1+ year(s) data-science experience (e.g., managing str… OR Master's Degree in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field AND 1+ year(s) data-science experience (e.g., managing structured and unstructured data, applying statistical techniques and reporting results) or consulting experience
- OR Bachelor's Degree in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field AND 2+ years data-science experience (e.g., managing str… OR Bachelor's Degree in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field AND 2+ years data-science experience (e.g., managing structured and unstructured data, applying statistical techniques and reporting results)
- OR equivalent experience.
What you'd do
- Data Analysis & Modeling: Analyze large-scale datasets to identify patterns, trends, and opportunities for improving yield and efficiency.
- Yield Optimization: Develop machine learning models to optimize resource allocation and pricing strategies.
- Cross-Functional Collaboration: Partner with business planning, engineering, product management, and finance teams to align yield strategies with business objectives.
- Experimentation & A/B Testing: Design and execute experiments to validate optimization hypotheses. Build causal inference models (e.g., difference-in-difference, synthetic control) to measure the impa… Experimentation & A/B Testing: Design and execute experiments to validate optimization hypotheses. Build causal inference models (e.g., difference-in-difference, synthetic control) to measure the impact of business decisions.
Nice to have
- Doctorate in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field AND 1+ year(s) data-science experience (e.g., managing structured a… Doctorate in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field AND 1+ year(s) data-science experience (e.g., managing structured and unstructured data, applying statistical techniques and reporting results)
- OR Master's Degree in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field AND 3+ years data-science experience (e.g., managing struc… OR Master's Degree in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field AND 3+ years data-science experience (e.g., managing structured and unstructured data, applying statistical techniques and reporting results)
- OR Bachelor's Degree in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field AND 5+ years data-science experience (e.g., managing str… OR Bachelor's Degree in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field AND 5+ years data-science experience (e.g., managing structured and unstructured data, applying statistical techniques and reporting results)
- Experience in Python, R, or similar languages
Tasks you're prepared for
(15 of 16 for Data Scientists)
- Analyze, manipulate, or process large sets of data using statistical software.
-
Apply feature selection algorithms to models predicting outcomes of interest, such as sales, attrition, and healthcare use.
via CSCD 484
- Apply sampling techniques to determine groups to be surveyed or use complete enumeration methods.
- Clean and manipulate raw data using statistical software.
- Compare models using statistical performance metrics, such as loss functions or proportion of explained variance.
+10 more covered tasks
Tasks you'd need to develop
(1)
Recommend data-driven solutions to key stakeholders.
These could be filled by an applied project, elective, or internship — see the program page for examples.
15/16
tasks
AIML - ML Engineer, Responsible AI
Apple
Seattle, WA
2026-06-04
Weekly Hours: 40 Role Number: 200642026-3337 Summary Would you like to play a part in building the next generation of generative AI applications at Apple? We're looking for scientists and engineers to work on ambitious projects that will impact the future of Apple, our products,
Requirements
- Strong engineering skills and experience in writing production-quality code in Python, Swift or other programming languages
- Background in generative models, natural language processing, LLMs, or diffusion models
- Experience with failure analysis, quality engineering, or robustness analysis for AI/ML based features
- Experience working with crowd-based annotations and human evaluations
What you'd do
- Would you like to play a part in building the next generation of generative AI applications at Apple? We're looking for scientists and engineers to work on ambitious projects that will impact the futu… Would you like to play a part in building the next generation of generative AI applications at Apple? We're looking for scientists and engineers to work on ambitious projects that will impact the future of Apple, our products, and the broader world.
- In this role, you'll have the opportunity to tackle innovative problems in machine learning, particularly focused on generative AI. As a member of the Apple HCMI group, you will be working on Apple's … In this role, you'll have the opportunity to tackle innovative problems in machine learning, particularly focused on generative AI. As a member of the Apple HCMI group, you will be working on Apple's generative models that will power a wide array of new features. Our team is currently working on large generative models for vision and language, with particular interest on safety, robustness, and uncertainty in models.
- Develop models, tools, metrics, and datasets for assessing and evaluating the safety of generative models over the model deployment lifecycle
- Develop methods, models, and tools to interpret and explain failures in language and diffusion models
Nice to have
- BS, MS or PhD in Computer Science, Machine Learning, or related fields or an equivalent qualification acquired through other avenues
- Proven track record of contributing to diverse teams in a collaborative environment
Tasks you're prepared for
(15 of 16 for Data Scientists)
- Analyze, manipulate, or process large sets of data using statistical software.
-
Apply feature selection algorithms to models predicting outcomes of interest, such as sales, attrition, and healthcare use.
via CSCD 484
- Apply sampling techniques to determine groups to be surveyed or use complete enumeration methods.
- Clean and manipulate raw data using statistical software.
- Compare models using statistical performance metrics, such as loss functions or proportion of explained variance.
+10 more covered tasks
Tasks you'd need to develop
(1)
Recommend data-driven solutions to key stakeholders.
These could be filled by an applied project, elective, or internship — see the program page for examples.
15/16
tasks
AI and Data Science Engineer II
Deloitte
Seattle, WA
2026-06-04
Our Deloitte Customer team empowers organizations to build deeper relationships with customers through innovative strategies, advanced analytics, Generative AI, transformative technologies, and creative design. We can enhance customer experiences and drive sustained growth and customer value creatio
Requirements
- Bachelor's degree in engineering, mathematics, physics, machine learning, statistics, computer science, or another quantitative field
- 2+ years of industry experience outside of academia applying data science or machine learning methods
- Experience translating business goals into machine learning use cases and model design
- Experience performing exploratory data analysis and developing predictive models
Nice to have
- Master's degree in engineering, mathematics, physics, machine learning, statistics, computer science, or another quantitative field
- Experience manipulating large marketing data sets and performing extract, transform, and load activities
- Experience with boosted trees, logistic regression, classification techniques, unsupervised models, large language models, or experimental design
- Experience with data sets generated in advertising technology or marketing technology environments
Tasks you're prepared for
(15 of 16 for Data Scientists)
- Analyze, manipulate, or process large sets of data using statistical software.
-
Apply feature selection algorithms to models predicting outcomes of interest, such as sales, attrition, and healthcare use.
via CSCD 484
- Apply sampling techniques to determine groups to be surveyed or use complete enumeration methods.
- Clean and manipulate raw data using statistical software.
- Compare models using statistical performance metrics, such as loss functions or proportion of explained variance.
+10 more covered tasks
Tasks you'd need to develop
(1)
Recommend data-driven solutions to key stakeholders.
These could be filled by an applied project, elective, or internship — see the program page for examples.
15/16
tasks
Product Data Science Intern
FlightSafety International Inc
Seattle, WA
2026-06-03
Company Overview Docusign brings agreements to life. Over 1.5 million customers and more than a billion people in over 180 countries use Docusign solutions to accelerate the process of doing business and simplify people's lives. With intelligent agreement management, Docusign unleashes business-cr
What you'd do
- 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 maki… 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
Tasks you're prepared for
(15 of 16 for Data Scientists)
- Analyze, manipulate, or process large sets of data using statistical software.
-
Apply feature selection algorithms to models predicting outcomes of interest, such as sales, attrition, and healthcare use.
via CSCD 484
- Apply sampling techniques to determine groups to be surveyed or use complete enumeration methods.
- Clean and manipulate raw data using statistical software.
- Compare models using statistical performance metrics, such as loss functions or proportion of explained variance.
+10 more covered tasks
Tasks you'd need to develop
(1)
Recommend data-driven solutions to key stakeholders.
These could be filled by an applied project, elective, or internship — see the program page for examples.
15/16
tasks
Machine Learning Engineer
FlightSafety International Inc
Seattle, WA
2026-06-03
Company Overview Docusign brings agreements to life. Over 1.5 million customers and more than a billion people in over 180 countries use Docusign solutions to accelerate the process of doing business and simplify people's lives. With intelligent agreement management, Docusign unleashes business-cr
What you'd do
- As a Machine Learning Engineer on the AI Platform team, you will design and build the foundational infrastructure that powers Docusign's next generation of intelligent systems. You will bridge the gap… As a Machine Learning Engineer on the AI Platform team, you will design and build the foundational infrastructure that powers Docusign's next generation of intelligent systems. You will bridge the gap between core AI research and production-grade engineering, developing scalable platforms for autonomous agents, advanced retrieval systems, and automated model optimization.
- This position is an individual contributor role reporting to the
- Director, Machine Learning Engineering
- *Responsibility
Nice to have
- Experience with distributed task queues or stateful workflow engines for managing complex, multi-step AI processes
- Experience with frameworks designed for horizontal scaling of compute-intensive ML workloads
- Experience designing "agent-loop" architectures that involve tool-use, self-correction, and multi-step reasoning
- Familiarity with vector storage systems and high-throughput data processing pipelines
Tasks you're prepared for
(15 of 16 for Data Scientists)
- Analyze, manipulate, or process large sets of data using statistical software.
-
Apply feature selection algorithms to models predicting outcomes of interest, such as sales, attrition, and healthcare use.
via CSCD 484
- Apply sampling techniques to determine groups to be surveyed or use complete enumeration methods.
- Clean and manipulate raw data using statistical software.
- Compare models using statistical performance metrics, such as loss functions or proportion of explained variance.
+10 more covered tasks
Tasks you'd need to develop
(1)
Recommend data-driven solutions to key stakeholders.
These could be filled by an applied project, elective, or internship — see the program page for examples.
15/16
tasks
Data Scientist
iSpot.tv, INC.
Bellevue, WA
2026-06-02
Implement industry-standard predictive modeling solutions. Analyze, manipulate, clean, and process large and messy data using predictive modeling solutions and cloud-based computing resources/infrastructure to scale and optimize data science tools and pipelines. Code original R/Python scripts, optim
Tasks you're prepared for
(15 of 16 for Data Scientists)
- Analyze, manipulate, or process large sets of data using statistical software.
-
Apply feature selection algorithms to models predicting outcomes of interest, such as sales, attrition, and healthcare use.
via CSCD 484
- Apply sampling techniques to determine groups to be surveyed or use complete enumeration methods.
- Clean and manipulate raw data using statistical software.
- Compare models using statistical performance metrics, such as loss functions or proportion of explained variance.
+10 more covered tasks
Tasks you'd need to develop
(1)
Recommend data-driven solutions to key stakeholders.
These could be filled by an applied project, elective, or internship — see the program page for examples.
15/16
tasks
Machine Learning Engineer, Monetization Engineering
Pinterest, Inc.
Seattle, WA
2026-06-02
About Pinterest: Millions of people around the world come to our platform to find creative ideas, dream about new possibilities and plan for memories that will last a lifetime. At Pinterest, we're on a mission to bring everyone the inspiration to create a life they love, and that starts with t
Requirements
- 2+ years of industry experience applying machine learning methods (e.g., user modeling, personalization, recommender systems, search, ranking, natural language processing, reinforcement learning, and … 2+ years of industry experience applying machine learning methods (e.g., user modeling, personalization, recommender systems, search, ranking, natural language processing, reinforcement learning, and graph representation learning)
- Degree in computer science, machine learning, statistics, or related field
- End-to-end hands-on experience with building data processing pipelines, large scale machine learning systems, and big data technologies (e.g., Hadoop/Spark)
- Practical knowledge of large scale recommender systems, or modern ads ranking, retrieval, targeting, marketplace systems
What you'd do
- Build cutting edge technology using the latest advances in deep learning and machine learning to personalize Pinterest
- Partner closely with teams across Pinterest to experiment and improve ML models for various product surfaces (Homefeed, Ads, Growth, Shopping, and Search), while gaining knowledge of how ML works in different areas
- Use data driven methods and leverage the unique properties of our data to improve candidates retrieval
- Work in a high-impact environment with quick experimentation and product launches
Nice to have
- Publications at top ML conferences
- Experience using Cursor, Copilot, Codex, or similar AI coding assistants for development, debugging, testing, and refactoring
- Familiarity with LLM-powered productivity tools for documentation search, experiment analysis, SQL/data exploration, and engineering workflow acceleration
- Expertise in scalable realtime systems that process stream data
Tasks you're prepared for
(15 of 16 for Data Scientists)
- Analyze, manipulate, or process large sets of data using statistical software.
-
Apply feature selection algorithms to models predicting outcomes of interest, such as sales, attrition, and healthcare use.
via CSCD 484
- Apply sampling techniques to determine groups to be surveyed or use complete enumeration methods.
- Clean and manipulate raw data using statistical software.
- Compare models using statistical performance metrics, such as loss functions or proportion of explained variance.
+10 more covered tasks
Tasks you'd need to develop
(1)
Recommend data-driven solutions to key stakeholders.
These could be filled by an applied project, elective, or internship — see the program page for examples.
15/16
tasks
Data Scientist, PPE Product Intelligence
Amazon
Seattle, WA
2026-06-02
Description Amazon's Price Perception and Evaluation team is seeking a driven Data Scientist to harness planet scale multi-modal datasets, and navigate a continuously evolving competitor landscape, in order to build and scale an advanced self-learning scientific price estimation and product unders
Requirements
- 1+ years of data querying languages (e.g. SQL), scripting languages (e.g. Python) or statistical/mathematical software (e.g. R, SAS, Matlab, etc.) experience
- 2+ years of data/research scientist, statistician or quantitative analyst in an internet-based company with complex and big data sources experience
- Bachelor's degree
What you'd do
- Design and run rigorous experiments at scale to evaluate and improve foundation model performance across hundreds of millions of products, geographies, and business verticals
- Lead the end-to-end lifecycle of evaluation models - from research and experimentation through production launch - including defining success metrics, obtaining stakeholder sign-off, and managing rollout
- Conduct online and offline labs to measure the real-world impact of model improvements beyond accuracy, including downstream supply chain, inventory, and financial outcomes
- Develop and deploy production-grade statistical models using Python, Scala, SQL, and related tools
Nice to have
- Knowledge of statistical packages and business intelligence tools such as SPSS, SAS, S-PLUS, or R
- Experience with clustered data processing (e.g., Hadoop, Spark, Map-reduce, and Hive)
Tasks you're prepared for
(15 of 16 for Data Scientists)
- Analyze, manipulate, or process large sets of data using statistical software.
-
Apply feature selection algorithms to models predicting outcomes of interest, such as sales, attrition, and healthcare use.
via CSCD 484
- Apply sampling techniques to determine groups to be surveyed or use complete enumeration methods.
- Clean and manipulate raw data using statistical software.
- Compare models using statistical performance metrics, such as loss functions or proportion of explained variance.
+10 more covered tasks
Tasks you'd need to develop
(1)
Recommend data-driven solutions to key stakeholders.
These could be filled by an applied project, elective, or internship — see the program page for examples.
15/16
tasks
Data Scientist, PPE Product Intelligence
Amazon
Seattle, WA
2026-05-31
Description Amazon's Price Perception and Evaluation team is seeking a driven Data Scientist to harness planet scale multi-modal datasets, and navigate a continuously evolving competitor landscape, in order to build and scale an advanced self-learning scientific price estimation and product unders
Requirements
- 3+ years of data querying languages (e.g. SQL), scripting languages (e.g. Python) or statistical/mathematical software (e.g. R, SAS, Matlab, etc.) experience
- 2+ years of data scientist experience
- 3+ years of machine learning/statistical modeling data analysis tools and techniques, and parameters that affect their performance experience
- Experience applying theoretical models in an applied environment
What you'd do
- Design and run rigorous experiments at scale to evaluate and improve foundation model performance across hundreds of millions of products, geographies, and business verticals
- Lead the end-to-end lifecycle of evaluation models - from research and experimentation through production launch - including defining success metrics, obtaining stakeholder sign-off, and managing rollout
- Conduct online and offline labs to measure the real-world impact of model improvements beyond accuracy, including downstream supply chain, inventory, and financial outcomes
- Develop and deploy production-grade statistical models using Python, Scala, SQL, and related tools
Nice to have
- Experience in Python, Perl, or another scripting language
- Experience in a ML or data scientist role with a large technology company
Tasks you're prepared for
(15 of 16 for Data Scientists)
- Analyze, manipulate, or process large sets of data using statistical software.
-
Apply feature selection algorithms to models predicting outcomes of interest, such as sales, attrition, and healthcare use.
via CSCD 484
- Apply sampling techniques to determine groups to be surveyed or use complete enumeration methods.
- Clean and manipulate raw data using statistical software.
- Compare models using statistical performance metrics, such as loss functions or proportion of explained variance.
+10 more covered tasks
Tasks you'd need to develop
(1)
Recommend data-driven solutions to key stakeholders.
These could be filled by an applied project, elective, or internship — see the program page for examples.
15/16
tasks
Consultant - Data Science / Data Lake
Deloitte
Seattle, WA
2026-05-31
Consultant - Data Science / Data Lake Are you looking to apply cyber analytics, artificial intelligence, and security operations experience in a client-facing role? At Deloitte, you'll help organizations modernize security operations, improve cyber resilience, and use data-driven insights to stren
Requirements
- 2+ years of experience in analytics consulting, cybersecurity analytics, security operations, or a combination of these (including internships and in-school experience)
- 1+ years of experience with artificial intelligence development tools or frameworks such as vector databases, LangChain, or CrewAI
- 1+ years of experience using Python, Structured Query Language (SQL), R, or SAS to prepare data for analysis, engineer features, visualize data, or support machine learning workflows
- Experience working with cybersecurity cloud platforms such as Google SecOps, Amazon Web Services (AWS), or Microsoft Azure, and exposure to security operations center (SOC) threat hunting or incident response
Nice to have
- Experience supporting the design, development, or deployment of enterprise data science or artificial intelligence solutions
- Experience applying artificial intelligence, machine learning, or advanced data engineering to cybersecurity use cases such as detection engineering or threat response support
- Experience parsing and normalizing cyber or information technology telemetry datasets
- Experience with PyTorch, Keras, TensorFlow, Scikit-learn, NumPy, or SciPy
Tasks you're prepared for
(15 of 16 for Data Scientists)
- Analyze, manipulate, or process large sets of data using statistical software.
-
Apply feature selection algorithms to models predicting outcomes of interest, such as sales, attrition, and healthcare use.
via CSCD 484
- Apply sampling techniques to determine groups to be surveyed or use complete enumeration methods.
- Clean and manipulate raw data using statistical software.
- Compare models using statistical performance metrics, such as loss functions or proportion of explained variance.
+10 more covered tasks
Tasks you'd need to develop
(1)
Recommend data-driven solutions to key stakeholders.
These could be filled by an applied project, elective, or internship — see the program page for examples.
15/16
tasks
Data Scientist - 3035128
Apex Systems, Inc.
Redmond, WA
2026-05-30
Job#: 3035128 Job Description: We are seeking a Data Scientist who is passionate about delivering high-impact, high-quality results to join the Player Data and Insights team. In this role, you will drive insights that inform the Game Studio strategy, with a focus on Consumer Products, Ou
Requirements
- 5 years of experience in data analytics.
- 5 years of experience with SQL, bonus if familiar with SparkSQL, Databricks, or Azure Data Explorer.
- 2 years of experience with dashboarding tools, PowerBI preferred.
- Proficient in Python, bonus if familiar with PySpark.
What you'd do
- We are seeking a Data Scientist who is passionate about delivering high-impact, high-quality results to join the Player Data and Insights team. In this role, you will drive insights that inform the Ga… We are seeking a Data Scientist who is passionate about delivering high-impact, high-quality results to join the Player Data and Insights team. In this role, you will drive insights that inform the Game Studio strategy, with a focus on Consumer Products, Out of Game Experiences and Partnerships. You'll collaborate closely with the stakeholder teams to enhance consumer products reporting, analyze out of game experiences, evaluate opportunities, and recommend data-drive strategies to level up the connection between all parts of the franchise. This role is additional coverage for a team member on maternity leave, and you will be taking over additional duties beyond this specific scope as needed. These include maintaining forecasting models, assisting in franchise reporting and estimation, and collaborating with other data science vendors in the Beyond the Game space. Specific responsibilities include making recommendations to optimize business performance and evaluating the impact of various programs and initiatives on critical metrics, including tying out of game activities to in-game metrics. The ideal candidate will have experience with statistical analysis, data visualization tools, and strong communication skills to translate insights into actionable recommendations for both technical and non-technical stakeholders.
- Partner with Consumer Products team and PADI data engineering to turn our Consumer Products data into clear reporting and actionable insights.
- Identify key learnings from your analysis and synthesize them into recommendations for stakeholders.
- Work collaboratively with other PADI data scientists to incorporate Beyond the Game findings into relevant major analyses and franchise beats.
Tasks you're prepared for
(15 of 16 for Data Scientists)
- Analyze, manipulate, or process large sets of data using statistical software.
-
Apply feature selection algorithms to models predicting outcomes of interest, such as sales, attrition, and healthcare use.
via CSCD 484
- Apply sampling techniques to determine groups to be surveyed or use complete enumeration methods.
- Clean and manipulate raw data using statistical software.
- Compare models using statistical performance metrics, such as loss functions or proportion of explained variance.
+10 more covered tasks
Tasks you'd need to develop
(1)
Recommend data-driven solutions to key stakeholders.
These could be filled by an applied project, elective, or internship — see the program page for examples.
15/16
tasks
Data Scientist
Deloitte
Portland, OR
2026-05-30
Are you an experienced, passionate pioneer in technology who wants to work in a collaborative environment? As an experienced Data Scientist, you will have the ability to share new ideas and collaborate on projects as a consultant without the extensive demands of travel. The Project Talent Model is d
Requirements
- Bachelor's degree, preferably in Computer Science, Information Technology, Computer Engineering, or related IT discipline; or equivalent experience
- 5+ Years of Experience in a Data Science or Machine Learning role.
- 5+ Years of Experience Proficiency in programming languages such as Python or R.
- 5+ Years of Experience with Strong knowledge of machine learning techniques and algorithms.
What you'd do
- Work with stakeholders to identify business problems and formulate them as data science challenges.
- Collect, clean, and explore large datasets to uncover trends and patterns.
- Develop and train machine learning models to solve problems such as prediction, classification, and clustering.
- Validate and deploy models into production environments.
Tasks you're prepared for
(15 of 16 for Data Scientists)
- Analyze, manipulate, or process large sets of data using statistical software.
-
Apply feature selection algorithms to models predicting outcomes of interest, such as sales, attrition, and healthcare use.
via CSCD 484
- Apply sampling techniques to determine groups to be surveyed or use complete enumeration methods.
- Clean and manipulate raw data using statistical software.
- Compare models using statistical performance metrics, such as loss functions or proportion of explained variance.
+10 more covered tasks
Tasks you'd need to develop
(1)
Recommend data-driven solutions to key stakeholders.
These could be filled by an applied project, elective, or internship — see the program page for examples.
15/16
tasks
Data Scientist
Deloitte
Bellevue, WA
2026-05-30
Are you an experienced, passionate pioneer in technology who wants to work in a collaborative environment? As an experienced Data Scientist, you will have the ability to share new ideas and collaborate on projects as a consultant without the extensive demands of travel. The Project Talent Model is d
Requirements
- Bachelor's degree, preferably in Computer Science, Information Technology, Computer Engineering, or related IT discipline; or equivalent experience
- 5+ Years of Experience in a Data Science or Machine Learning role.
- 5+ Years of Experience Proficiency in programming languages such as Python or R.
- 5+ Years of Experience with Strong knowledge of machine learning techniques and algorithms.
What you'd do
- Work with stakeholders to identify business problems and formulate them as data science challenges.
- Collect, clean, and explore large datasets to uncover trends and patterns.
- Develop and train machine learning models to solve problems such as prediction, classification, and clustering.
- Validate and deploy models into production environments.
Tasks you're prepared for
(15 of 16 for Data Scientists)
- Analyze, manipulate, or process large sets of data using statistical software.
-
Apply feature selection algorithms to models predicting outcomes of interest, such as sales, attrition, and healthcare use.
via CSCD 484
- Apply sampling techniques to determine groups to be surveyed or use complete enumeration methods.
- Clean and manipulate raw data using statistical software.
- Compare models using statistical performance metrics, such as loss functions or proportion of explained variance.
+10 more covered tasks
Tasks you'd need to develop
(1)
Recommend data-driven solutions to key stakeholders.
These could be filled by an applied project, elective, or internship — see the program page for examples.
15/16
tasks
Data Scientist
Deloitte
Boise, ID
2026-05-30
Are you an experienced, passionate pioneer in technology who wants to work in a collaborative environment? As an experienced Data Scientist, you will have the ability to share new ideas and collaborate on projects as a consultant without the extensive demands of travel. The Project Talent Model is d
Requirements
- Bachelor's degree, preferably in Computer Science, Information Technology, Computer Engineering, or related IT discipline; or equivalent experience
- 5+ Years of Experience in a Data Science or Machine Learning role.
- 5+ Years of Experience Proficiency in programming languages such as Python or R.
- 5+ Years of Experience with Strong knowledge of machine learning techniques and algorithms.
What you'd do
- Work with stakeholders to identify business problems and formulate them as data science challenges.
- Collect, clean, and explore large datasets to uncover trends and patterns.
- Develop and train machine learning models to solve problems such as prediction, classification, and clustering.
- Validate and deploy models into production environments.
Tasks you're prepared for
(15 of 16 for Data Scientists)
- Analyze, manipulate, or process large sets of data using statistical software.
-
Apply feature selection algorithms to models predicting outcomes of interest, such as sales, attrition, and healthcare use.
via CSCD 484
- Apply sampling techniques to determine groups to be surveyed or use complete enumeration methods.
- Clean and manipulate raw data using statistical software.
- Compare models using statistical performance metrics, such as loss functions or proportion of explained variance.
+10 more covered tasks
Tasks you'd need to develop
(1)
Recommend data-driven solutions to key stakeholders.
These could be filled by an applied project, elective, or internship — see the program page for examples.
15/16
tasks
Machine Learning Research Scientist - Health AIML
Apple
Seattle, WA
2026-05-30
Role Number: 200665930-3337 Summary The Health AIML team is at the forefront of machine learning and health science at Apple. We are a close-knit team of research scientists, software engineers and machine learning engineers passionate about delivering innovative technologies that impac
Requirements
- PhD in Computer Science/Engineering, Machine Learning, Statistics, Mathematics or related field.
- Industry work experience.
- Experience landing contributions to major LLM training runs.
- Proven track record of publishing SOTA.
What you'd do
- The Health AIML team is at the forefront of machine learning and health science at Apple. We are a close-knit team of research scientists, software engineers and machine learning engineers passionate … The Health AIML team is at the forefront of machine learning and health science at Apple. We are a close-knit team of research scientists, software engineers and machine learning engineers passionate about delivering innovative technologies that impact millions of users. We are looking for a Machine Learning Research Scientist with strong dedication to solving real-world problems in health and fitness that enrich our customers' lives.
- We're developing next-generation multimodal models to create intelligent health and fitness experiences. This role requires someone with strong expertise in large multimodal models to work at the inte… We're developing next-generation multimodal models to create intelligent health and fitness experiences. This role requires someone with strong expertise in large multimodal models to work at the intersection of AI and health to build foundational models that scale to billions of users worldwide. Your work will shape the future of health and fitness technologies at Apple. We are looking for a senior researcher to guide multimodality research. You will focus on the development of foundational technology that enables models to understand health and fitness data.
Nice to have
- Experience in training and evaluating multimodal models.
- Understand of time-series modeling, self-supervised learning, and cross-modal training.
- Ability to thoroughly evaluate and improve deep learning architectures in a self-directed fashion.
- Motivated by safely deploying LLMs in the health and fitness space.
Tasks you're prepared for
(15 of 16 for Data Scientists)
- Analyze, manipulate, or process large sets of data using statistical software.
-
Apply feature selection algorithms to models predicting outcomes of interest, such as sales, attrition, and healthcare use.
via CSCD 484
- Apply sampling techniques to determine groups to be surveyed or use complete enumeration methods.
- Clean and manipulate raw data using statistical software.
- Compare models using statistical performance metrics, such as loss functions or proportion of explained variance.
+10 more covered tasks
Tasks you'd need to develop
(1)
Recommend data-driven solutions to key stakeholders.
These could be filled by an applied project, elective, or internship — see the program page for examples.
15/16
tasks
Data Scientist
Deloitte
Seattle, WA
2026-05-30
Are you an experienced, passionate pioneer in technology who wants to work in a collaborative environment? As an experienced Data Scientist, you will have the ability to share new ideas and collaborate on projects as a consultant without the extensive demands of travel. The Project Talent Model is d
Requirements
- Bachelor's degree, preferably in Computer Science, Information Technology, Computer Engineering, or related IT discipline; or equivalent experience
- 5+ Years of Experience in a Data Science or Machine Learning role.
- 5+ Years of Experience Proficiency in programming languages such as Python or R.
- 5+ Years of Experience with Strong knowledge of machine learning techniques and algorithms.
What you'd do
- Work with stakeholders to identify business problems and formulate them as data science challenges.
- Collect, clean, and explore large datasets to uncover trends and patterns.
- Develop and train machine learning models to solve problems such as prediction, classification, and clustering.
- Validate and deploy models into production environments.
Tasks you're prepared for
(15 of 16 for Data Scientists)
- Analyze, manipulate, or process large sets of data using statistical software.
-
Apply feature selection algorithms to models predicting outcomes of interest, such as sales, attrition, and healthcare use.
via CSCD 484
- Apply sampling techniques to determine groups to be surveyed or use complete enumeration methods.
- Clean and manipulate raw data using statistical software.
- Compare models using statistical performance metrics, such as loss functions or proportion of explained variance.
+10 more covered tasks
Tasks you'd need to develop
(1)
Recommend data-driven solutions to key stakeholders.
These could be filled by an applied project, elective, or internship — see the program page for examples.
15/16
tasks
Machine Learning Engineer, Level 4
Snap Inc.
Bellevue, WA
2026-05-29
Snap Inc (https://www.snap.com/en-US/) is a technology company. We believe the camera presents the greatest opportunity to improve the way people live and communicate. Snap contributes to human progress by empowering people to express themselves, live in the moment, learn about the world, and have
Requirements
- Bachelor's Degree in a relevant technical field such as computer science or equivalent years of practical work experience
- 3+ years of post-Bachelor's machine learning experience; or Master's degree in a technical field + 2+ year of post-grad machine learning experience; or PhD in a relevant technical field
- Experience developing machine learning models for ranking, recommendations, search, content understanding, image generation, or other relevant applications of machine learning
What you'd do
- Build and deploy machine learning models that power core products, serving millions of Snapchatters
- Apply modern ML techniques to solve large-scale, real-world problems
- Own the full ML lifecycle from data analysis to production deployment
- Partner with cross-functional teams to prototype and launch ML-driven features
Nice to have
- Advanced degree in computer science or related field
- Experience working with machine learning frameworks such as TensorFlow, Caffe2, PyTorch, Spark ML, scikit-learn, or related frameworks
- Experience working with machine learning, ranking infrastructures, and system design
Tasks you're prepared for
(15 of 16 for Data Scientists)
- Analyze, manipulate, or process large sets of data using statistical software.
-
Apply feature selection algorithms to models predicting outcomes of interest, such as sales, attrition, and healthcare use.
via CSCD 484
- Apply sampling techniques to determine groups to be surveyed or use complete enumeration methods.
- Clean and manipulate raw data using statistical software.
- Compare models using statistical performance metrics, such as loss functions or proportion of explained variance.
+10 more covered tasks
Tasks you'd need to develop
(1)
Recommend data-driven solutions to key stakeholders.
These could be filled by an applied project, elective, or internship — see the program page for examples.
15/16
tasks
Data Scientist, Demand Forecasting
Amazon
Bellevue, WA
2026-05-29
Description What does it take to build a foundation model that can forecast demand for hundreds of millions of products - including ones that have never been sold before? At Amazon, our Demand Forecasting team is tackling one of the most ambitious challenges in applied time series research: buil
Requirements
- 1+ years of data querying languages (e.g. SQL), scripting languages (e.g. Python) or statistical/mathematical software (e.g. R, SAS, Matlab, etc.) experience
- 2+ years of data/research scientist, statistician or quantitative analyst in an internet-based company with complex and big data sources experience
- Bachelor's degree
What you'd do
- Design and run rigorous experiments at scale to evaluate and improve foundation model performance across hundreds of millions of products, geographies, and business verticals
- Lead the end-to-end lifecycle of forecasting models - from research and experimentation through production launch - including defining success metrics, obtaining stakeholder sign-off, and managing rollout
- Conduct online and offline labs to measure the real-world impact of forecast improvements beyond accuracy, including downstream supply chain, inventory, and financial outcomes
- Develop and deploy production-grade deep learning and statistical models using Python, Scala, SQL, and related tools
Nice to have
- Knowledge of statistical packages and business intelligence tools such as SPSS, SAS, S-PLUS, or R
- Experience with clustered data processing (e.g., Hadoop, Spark, Map-reduce, and Hive)
Tasks you're prepared for
(15 of 16 for Data Scientists)
- Analyze, manipulate, or process large sets of data using statistical software.
-
Apply feature selection algorithms to models predicting outcomes of interest, such as sales, attrition, and healthcare use.
via CSCD 484
- Apply sampling techniques to determine groups to be surveyed or use complete enumeration methods.
- Clean and manipulate raw data using statistical software.
- Compare models using statistical performance metrics, such as loss functions or proportion of explained variance.
+10 more covered tasks
Tasks you'd need to develop
(1)
Recommend data-driven solutions to key stakeholders.
These could be filled by an applied project, elective, or internship — see the program page for examples.
15/16
tasks
Data Scientist I, PXT Central Science
Amazon
Bellevue, WA
2026-05-29
Description PXT Central Science is seeking an exceptional Data Scientist to join our team. The ideal candidate will thrive in a dynamic, multifaceted role where you'll translate complex business challenges into rigorous quantitative frameworks, extract actionable insights from structured and unstr
Requirements
- 1+ years of data querying languages (e.g. SQL), scripting languages (e.g. Python) or statistical/mathematical software (e.g. R, SAS, Matlab, etc.) experience
- 2+ years of data/research scientist, statistician or quantitative analyst in an internet-based company with complex and big data sources experience
- 1+ years of creating or contributing to mathematical textbooks, research papers, or educational content experience
- Master's degree in Science, Technology, Engineering, or Mathematics (STEM), or experience working in Science, Technology, Engineering, or Mathematics (STEM)
What you'd do
- Own the design, development, and maintenance of scalable models and prototypes leveraging statistical, machine learning, or GenAI methodologies to enhance employee experience.
- Partner with scientists, engineers, and product leaders to solve for employee experience defects using scientific approaches, building new services and tools that deliverable measurable impact.
- Author and maintain detailed technical documentation related to the projects you drive.
- Communicate results to diverse audiences of varying technical background with effective writing, visualizations, and presentations
Nice to have
- Ph.D. in Science, Technology, Engineering, or Mathematics (STEM)
- Knowledge of statistical packages and business intelligence tools such as SPSS, SAS, S-PLUS, or R
- Knowledge of machine learning concepts and their application to reasoning and problem-solving
- Experience with clustered data processing (e.g., Hadoop, Spark, Map-reduce, and Hive)
Tasks you're prepared for
(15 of 16 for Data Scientists)
- Analyze, manipulate, or process large sets of data using statistical software.
-
Apply feature selection algorithms to models predicting outcomes of interest, such as sales, attrition, and healthcare use.
via CSCD 484
- Apply sampling techniques to determine groups to be surveyed or use complete enumeration methods.
- Clean and manipulate raw data using statistical software.
- Compare models using statistical performance metrics, such as loss functions or proportion of explained variance.
+10 more covered tasks
Tasks you'd need to develop
(1)
Recommend data-driven solutions to key stakeholders.
These could be filled by an applied project, elective, or internship — see the program page for examples.
15/16
tasks
Machine Learning Engineer, Level 4
Snap Inc.
Seattle, WA
2026-05-29
Snap Inc (https://www.snap.com/en-US/) is a technology company. We believe the camera presents the greatest opportunity to improve the way people live and communicate. Snap contributes to human progress by empowering people to express themselves, live in the moment, learn about the world, and have
Requirements
- Bachelor's Degree in a relevant technical field such as computer science or equivalent years of practical work experience
- 3+ years of post-Bachelor's machine learning experience; or Master's degree in a technical field + 2+ year of post-grad machine learning experience; or PhD in a relevant technical field
- Experience developing machine learning models for ranking, recommendations, search, content understanding, image generation, or other relevant applications of machine learning
What you'd do
- Build and deploy machine learning models that power core products, serving millions of Snapchatters
- Apply modern ML techniques to solve large-scale, real-world problems
- Own the full ML lifecycle from data analysis to production deployment
- Partner with cross-functional teams to prototype and launch ML-driven features
Nice to have
- Advanced degree in computer science or related field
- Experience working with machine learning frameworks such as TensorFlow, Caffe2, PyTorch, Spark ML, scikit-learn, or related frameworks
- Experience working with machine learning, ranking infrastructures, and system design
Tasks you're prepared for
(15 of 16 for Data Scientists)
- Analyze, manipulate, or process large sets of data using statistical software.
-
Apply feature selection algorithms to models predicting outcomes of interest, such as sales, attrition, and healthcare use.
via CSCD 484
- Apply sampling techniques to determine groups to be surveyed or use complete enumeration methods.
- Clean and manipulate raw data using statistical software.
- Compare models using statistical performance metrics, such as loss functions or proportion of explained variance.
+10 more covered tasks
Tasks you'd need to develop
(1)
Recommend data-driven solutions to key stakeholders.
These could be filled by an applied project, elective, or internship — see the program page for examples.
15/16
tasks
Data Scientist I, PXT Central Science
Amazon
Seattle, WA
2026-05-29
Description PXT Central Science is seeking an exceptional Data Scientist to join our team. The ideal candidate will thrive in a dynamic, multifaceted role where you'll translate complex business challenges into rigorous quantitative frameworks, extract actionable insights from structured and unstr
Requirements
- 1+ years of data querying languages (e.g. SQL), scripting languages (e.g. Python) or statistical/mathematical software (e.g. R, SAS, Matlab, etc.) experience
- 2+ years of data/research scientist, statistician or quantitative analyst in an internet-based company with complex and big data sources experience
- 1+ years of creating or contributing to mathematical textbooks, research papers, or educational content experience
- Master's degree in Science, Technology, Engineering, or Mathematics (STEM), or experience working in Science, Technology, Engineering, or Mathematics (STEM)
What you'd do
- Own the design, development, and maintenance of scalable models and prototypes leveraging statistical, machine learning, or GenAI methodologies to enhance employee experience.
- Partner with scientists, engineers, and product leaders to solve for employee experience defects using scientific approaches, building new services and tools that deliverable measurable impact.
- Author and maintain detailed technical documentation related to the projects you drive.
- Communicate results to diverse audiences of varying technical background with effective writing, visualizations, and presentations
Nice to have
- Ph.D. in Science, Technology, Engineering, or Mathematics (STEM)
- Knowledge of statistical packages and business intelligence tools such as SPSS, SAS, S-PLUS, or R
- Knowledge of machine learning concepts and their application to reasoning and problem-solving
- Experience with clustered data processing (e.g., Hadoop, Spark, Map-reduce, and Hive)
Tasks you're prepared for
(15 of 16 for Data Scientists)
- Analyze, manipulate, or process large sets of data using statistical software.
-
Apply feature selection algorithms to models predicting outcomes of interest, such as sales, attrition, and healthcare use.
via CSCD 484
- Apply sampling techniques to determine groups to be surveyed or use complete enumeration methods.
- Clean and manipulate raw data using statistical software.
- Compare models using statistical performance metrics, such as loss functions or proportion of explained variance.
+10 more covered tasks
Tasks you'd need to develop
(1)
Recommend data-driven solutions to key stakeholders.
These could be filled by an applied project, elective, or internship — see the program page for examples.
15/16
tasks
Associate AI/ML Engineer
Raft LLC
Tacoma, WA
2026-05-28
This is a U.S. based position. All of the programs we support require U.S. citizenship to be eligible for employment. All work must be conducted within the continental U.S. Who we are: Raft (https://TeamRaft.com) is a customer-obsessed non-traditional defense tech company dedicated to em
Requirements
- 1+ years of relevant hands-on experience, or a PhD in a related field with demonstrated practical application
- Practical experience in Machine Learning models and Software Engineering
- A passion for (and track record of) innovation, an interest in exploring and leveraging new data modalities, and working across interdisciplinary teams
- Experience building and maintaining machine learning platforms and pipelines
What you'd do
- *AI/ML Engineer,
- you will collaborate with a cross-functional data team comprising of DevSecOps engineers, Product Owners, Data Engineers and Data Scientists. Your primary responsibility will be to develop machine lea… you will collaborate with a cross-functional data team comprising of DevSecOps engineers, Product Owners, Data Engineers and Data Scientists. Your primary responsibility will be to develop machine learning models that are integral to a larger pipeline delivering value to our end customers.
Nice to have
- Publications or GitHub repos showcasing your skills
Tasks you're prepared for
(15 of 16 for Data Scientists)
- Analyze, manipulate, or process large sets of data using statistical software.
-
Apply feature selection algorithms to models predicting outcomes of interest, such as sales, attrition, and healthcare use.
via CSCD 484
- Apply sampling techniques to determine groups to be surveyed or use complete enumeration methods.
- Clean and manipulate raw data using statistical software.
- Compare models using statistical performance metrics, such as loss functions or proportion of explained variance.
+10 more covered tasks
Tasks you'd need to develop
(1)
Recommend data-driven solutions to key stakeholders.
These could be filled by an applied project, elective, or internship — see the program page for examples.
15/16
tasks
AI/ML Engineer
Raft LLC
Tacoma, WA
2026-05-28
This is a U.S. based position. All of the programs we support require U.S. citizenship to be eligible for employment. All work must be conducted within the continental U.S. Who we are: Raft (https://TeamRaft.com) is a customer-obsessed non-traditional defense tech company dedicated to em
Requirements
- 3+ years of relevant hands-on experience, or a PhD in a related field with demonstrated practical application
- Practical experience in Machine Learning models and Software Engineering
- A passion for (and track record of) innovation, an interest in exploring and leveraging new data modalities, and working across interdisciplinary teams
- Experience building and maintaining machine learning platforms and pipelines
What you'd do
- *AI/ML Engineer,
- you will collaborate with a cross-functional data team comprising of DevSecOps engineers, Product Owners, Data Engineers and Data Scientists. Your primary responsibility will be to develop machine lea… you will collaborate with a cross-functional data team comprising of DevSecOps engineers, Product Owners, Data Engineers and Data Scientists. Your primary responsibility will be to develop machine learning models that are integral to a larger pipeline delivering value to our end customers.
Nice to have
- Publications or GitHub repos showcasing your skills
Tasks you're prepared for
(15 of 16 for Data Scientists)
- Analyze, manipulate, or process large sets of data using statistical software.
-
Apply feature selection algorithms to models predicting outcomes of interest, such as sales, attrition, and healthcare use.
via CSCD 484
- Apply sampling techniques to determine groups to be surveyed or use complete enumeration methods.
- Clean and manipulate raw data using statistical software.
- Compare models using statistical performance metrics, such as loss functions or proportion of explained variance.
+10 more covered tasks
Tasks you'd need to develop
(1)
Recommend data-driven solutions to key stakeholders.
These could be filled by an applied project, elective, or internship — see the program page for examples.
15/16
tasks
Business Data Scientist, Ads Marketing Analytics
Google
Kirkland, WA
2026-05-28
Business Data Scientist, Ads Marketing Analytics _corporate_fare_ Google _place_ Kirkland, WA, USA Mid Experience driving progress, solving problems, and mentoring more junior team members; deeper expertise and applied knowledge within relevant area. _info_outline_ XIn accordance with
Requirements
- Master's degree in a quantitative field (Statistics, Mathematics, Data Science, Bioinformatics, Economics, etc.) or equivalent practical experience
- 3 years of experience in a data science field.
- Experience with statistical software (e.g., R, Python, MATLAB) and database languages (i.e., SQL).
- Experience using analytics to solve product or business problems, querying databases or statistical analysis.
What you'd do
- 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 in… Google's leadership team hand-picks thorny business challenges, and members of BizOps work in small teams to find solutions. As part of this team you fully immerse yourself in data collection, draw insight from analysis, and then zoom out to develop compelling, synthesized recommendations. Taking strategy one step further, you also persuasively communicate your recommendations to senior-level executives, roll-up your sleeves to help drive implementation and check back-in to see the impact of your recommendations.
- Google Ads Marketing helps advertisers of all sizes succeed with digital marketing. In this role, you will work with a team to advance marketing science for customers using Google's advertising soluti… Google Ads Marketing helps advertisers of all sizes succeed with digital marketing. In this role, you will work with a team to advance marketing science for customers using Google's advertising solutions. This unique opportunity applies Data Science tools to accelerate Ads business growth, working cross-functionally with Sales, Marketing, and Product teams.
- As a Data Scientist on this team, you will perform deep data analytics, drive experimentation and measurement, and advance machine learning modeling to support global marketing programs.
- Collaborating with a multidisciplinary team of marketers, product managers, data scientists, and engineers, you will leverage underlying data to align on key metrics and methodologies. Your insights w… Collaborating with a multidisciplinary team of marketers, product managers, data scientists, and engineers, you will leverage underlying data to align on key metrics and methodologies. Your insights will enable marketers to develop highly effective programs. Using core Data Science expertise, you will design, prototype, and build scalable analysis pipelines to support campaigns. You will perform analytics, execute experimentation, and conduct incrementality measurement to inform strategic decisions across the entire Ads Marketing lifecycle-from acquisition and onboarding to growth and retention.
Nice to have
- PhD in Statistics or related quantitative discipline.
- 2 years of experience, including statistical data analysis such as generalized linear models, multivariate analysis, clustering/segmentation and sampling methods.
- Experience in controlled experiment design and causal inference methods.
- Ability to prioritize requests and partner well in an environment with competing demands from stakeholders.
Tasks you're prepared for
(15 of 16 for Data Scientists)
- Analyze, manipulate, or process large sets of data using statistical software.
-
Apply feature selection algorithms to models predicting outcomes of interest, such as sales, attrition, and healthcare use.
via CSCD 484
- Apply sampling techniques to determine groups to be surveyed or use complete enumeration methods.
- Clean and manipulate raw data using statistical software.
- Compare models using statistical performance metrics, such as loss functions or proportion of explained variance.
+10 more covered tasks
Tasks you'd need to develop
(1)
Recommend data-driven solutions to key stakeholders.
These could be filled by an applied project, elective, or internship — see the program page for examples.
15/16
tasks
Data Scientist II, Middle Mile Transportation Science team
Amazon
Bellevue, WA
2026-05-28
Description The NASC & TOM Science team owns Operations Research, Machine Learning, and AI projects across the North America Sort Center (NASC) and Transportation Operations Management (TOM) planning and operations organizations. We turn complex network, labor, and capacity problems into deployed
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
What you'd do
- 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;
Nice to have
- 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
Tasks you're prepared for
(15 of 16 for Data Scientists)
- Analyze, manipulate, or process large sets of data using statistical software.
-
Apply feature selection algorithms to models predicting outcomes of interest, such as sales, attrition, and healthcare use.
via CSCD 484
- Apply sampling techniques to determine groups to be surveyed or use complete enumeration methods.
- Clean and manipulate raw data using statistical software.
- Compare models using statistical performance metrics, such as loss functions or proportion of explained variance.
+10 more covered tasks
Tasks you'd need to develop
(1)
Recommend data-driven solutions to key stakeholders.
These could be filled by an applied project, elective, or internship — see the program page for examples.
15/16
tasks
Machine Learning Engineer, AWS Applied AI Solution
Amazon
Seattle, WA
2026-05-27
Description As part of the AWS Applied AI Solutions organization, our vision is to provide business applications, leveraging Amazon's unique experience and expertise, that are used by millions of companies worldwide to manage day-to-day operations. We accelerate our customers' businesses through d
Requirements
- 3+ years of non-internship professional software development experience
- 2+ years of non-internship design or architecture (design patterns, reliability and scaling) of new and existing systems experience
- 1+ years of software development engineer or related occupational experience
- 1+ years of designing and developing large-scale, multi-tiered, multi-threaded, embedded or distributed software applications, tools, systems, and services using: C#, C++, Java, or Perl experience
What you'd do
- Work closely with Applied Scientists and cross-functional engineering teams to transform research code into robust, scalable production systems
- Own end-to-end deployment at scale of Generative AI and ML methods, ensuring reliability and performance
- Establish scalable, efficient, automated processes for large-scale data analysis, machine learning model development, model validation and serving
- Research and implement innovative approaches for efficient model deployment, training, and optimization
Nice to have
- 3+ years of full software development life cycle, including coding standards, code reviews, source control management, build processes, testing, and operations experience
- Bachelor's degree in computer science or equivalent
Tasks you're prepared for
(15 of 16 for Data Scientists)
- Analyze, manipulate, or process large sets of data using statistical software.
-
Apply feature selection algorithms to models predicting outcomes of interest, such as sales, attrition, and healthcare use.
via CSCD 484
- Apply sampling techniques to determine groups to be surveyed or use complete enumeration methods.
- Clean and manipulate raw data using statistical software.
- Compare models using statistical performance metrics, such as loss functions or proportion of explained variance.
+10 more covered tasks
Tasks you'd need to develop
(1)
Recommend data-driven solutions to key stakeholders.
These could be filled by an applied project, elective, or internship — see the program page for examples.
15/16
tasks
Data Scientist, Product
OpenAI Inc.
Seattle, WA
2026-05-25
About the Team Our Applied team brings OpenAI technologies to consumers and businesses around the world. We collaborate across research, engineering, design and business functions to turn cutting-edge AI advancements into impactful real-world applications. Our team has been behind notable prod
What you'd do
- As a Data Scientist on the Applied Product team, you will contribute to a data-driven product development culture for consumer and enterprise products at OpenAI. This is critical as our products reach… As a Data Scientist on the Applied Product team, you will contribute to a data-driven product development culture for consumer and enterprise products at OpenAI. This is critical as our products reach millions of users and businesses worldwide. We are focused on aligning both research and product development to drive measurable impact for these individuals and organizations alike.
- You should expect to define our north-star metrics, design A/B tests, and establish source-of-truth dashboards that the entire company can use to answer their own product questions. Most importantly, … You should expect to define our north-star metrics, design A/B tests, and establish source-of-truth dashboards that the entire company can use to answer their own product questions. Most importantly, you should expect to be a core member of the product development team.
- This role is based in San Francisco, CA or Seattle, WA. We use a hybrid work model of 3 days in the office per week and offer relocation assistance to new employees.
- *In this role, you will:
Tasks you're prepared for
(15 of 16 for Data Scientists)
- Analyze, manipulate, or process large sets of data using statistical software.
-
Apply feature selection algorithms to models predicting outcomes of interest, such as sales, attrition, and healthcare use.
via CSCD 484
- Apply sampling techniques to determine groups to be surveyed or use complete enumeration methods.
- Clean and manipulate raw data using statistical software.
- Compare models using statistical performance metrics, such as loss functions or proportion of explained variance.
+10 more covered tasks
Tasks you'd need to develop
(1)
Recommend data-driven solutions to key stakeholders.
These could be filled by an applied project, elective, or internship — see the program page for examples.
15/16
tasks
Data Scientist III
Indeed
Portland, OR
2026-05-23
Our Mission As the world's number 1 job site*, our mission is to help people get jobs. We strive to cultivate an inclusive and accessible workplace where all people feel comfortable being themselves. We're looking to grow our teams with more people who share our enthusiasm for innovation and c
What you'd do
- As a Data Scientist III at Indeed, you will leverage your expertise in data science, statistics, AI and machine learning to take on complex product, marketing and business challenges. You will design … As a Data Scientist III at Indeed, you will leverage your expertise in data science, statistics, AI and machine learning to take on complex product, marketing and business challenges. You will design and implement analytical solutions that guide decisions, optimize product performance or marketing campaigns, and create measurable impact across the organization.
- You will work closely with engineering and product or marketing teams to identify opportunities, evaluate initiatives, and develop models and analyses that inform data-driven strategies. You will also… You will work closely with engineering and product or marketing teams to identify opportunities, evaluate initiatives, and develop models and analyses that inform data-driven strategies. You will also contribute to building best practices in data science and mentor others in the team, helping elevate the technical capabilities and impact of those around you.
- Oversee the design and execution of advanced analyses, experiments, and machine learning models to address complex questions.
- Translate data into actionable insights to guide product, marketing and business decisions.
Tasks you're prepared for
(15 of 16 for Data Scientists)
- Analyze, manipulate, or process large sets of data using statistical software.
-
Apply feature selection algorithms to models predicting outcomes of interest, such as sales, attrition, and healthcare use.
via CSCD 484
- Apply sampling techniques to determine groups to be surveyed or use complete enumeration methods.
- Clean and manipulate raw data using statistical software.
- Compare models using statistical performance metrics, such as loss functions or proportion of explained variance.
+10 more covered tasks
Tasks you'd need to develop
(1)
Recommend data-driven solutions to key stakeholders.
These could be filled by an applied project, elective, or internship — see the program page for examples.
15/16
tasks
Data Scientist III
Indeed
Boise, ID
2026-05-23
Our Mission As the world's number 1 job site*, our mission is to help people get jobs. We strive to cultivate an inclusive and accessible workplace where all people feel comfortable being themselves. We're looking to grow our teams with more people who share our enthusiasm for innovation and c
What you'd do
- As a Data Scientist III at Indeed, you will leverage your expertise in data science, statistics, AI and machine learning to take on complex product, marketing and business challenges. You will design … As a Data Scientist III at Indeed, you will leverage your expertise in data science, statistics, AI and machine learning to take on complex product, marketing and business challenges. You will design and implement analytical solutions that guide decisions, optimize product performance or marketing campaigns, and create measurable impact across the organization.
- You will work closely with engineering and product or marketing teams to identify opportunities, evaluate initiatives, and develop models and analyses that inform data-driven strategies. You will also… You will work closely with engineering and product or marketing teams to identify opportunities, evaluate initiatives, and develop models and analyses that inform data-driven strategies. You will also contribute to building best practices in data science and mentor others in the team, helping elevate the technical capabilities and impact of those around you.
- Oversee the design and execution of advanced analyses, experiments, and machine learning models to address complex questions.
- Translate data into actionable insights to guide product, marketing and business decisions.
Tasks you're prepared for
(15 of 16 for Data Scientists)
- Analyze, manipulate, or process large sets of data using statistical software.
-
Apply feature selection algorithms to models predicting outcomes of interest, such as sales, attrition, and healthcare use.
via CSCD 484
- Apply sampling techniques to determine groups to be surveyed or use complete enumeration methods.
- Clean and manipulate raw data using statistical software.
- Compare models using statistical performance metrics, such as loss functions or proportion of explained variance.
+10 more covered tasks
Tasks you'd need to develop
(1)
Recommend data-driven solutions to key stakeholders.
These could be filled by an applied project, elective, or internship — see the program page for examples.
15/16
tasks
Data Scientists - Finance
T-Mobile USA, Inc
Bellevue, WA
2026-05-23
At T-Mobile, we invest in YOU! Our Total Rewards Package ensures that employees get the same big love we give our customers. All team members receive a competitive base salary and compensation package - this is Total Rewards. Employees enjoy multiple wealth-building opportunities through our annual
Requirements
- (1) Applying statistical and mathematical methodologies including Linear Regression, Logistic Regression, Decision Tree, Cluster Analysis, and Hypothesis Testing to perform segmentation, prediction, f… (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. Pe… (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 interna… (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
What you'd do
- 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.
Tasks you're prepared for
(15 of 16 for Data Scientists)
- Analyze, manipulate, or process large sets of data using statistical software.
-
Apply feature selection algorithms to models predicting outcomes of interest, such as sales, attrition, and healthcare use.
via CSCD 484
- Apply sampling techniques to determine groups to be surveyed or use complete enumeration methods.
- Clean and manipulate raw data using statistical software.
- Compare models using statistical performance metrics, such as loss functions or proportion of explained variance.
+10 more covered tasks
Tasks you'd need to develop
(1)
Recommend data-driven solutions to key stakeholders.
These could be filled by an applied project, elective, or internship — see the program page for examples.
15/16
tasks
Data Scientist III - AMZ9442729
AMAZON.COM SERVICES LLC
Seattle, WA
2026-05-23
MULTIPLE POSITIONS AVAILABLE Employer: AMAZON.COM SERVICES LLC Offered Position: Data Scientist III Job Location: Seattle, Washington Job Number: AMZ9442729 Position Responsibilities: Own the data science elements of various products to help with data-based decision making, product perfo
Requirements
- Bachelor's degree or foreign equivalent degree in Statistics, Applied Mathematics, Economics, Engineering, Computer Science or a related field and two years of experience in the job offered or a relat… Bachelor's degree or foreign equivalent degree in Statistics, Applied Mathematics, Economics, Engineering, Computer Science or a related field and two years of experience in the job offered or a related occupation. Employer will accept four years of experience as equivalent to the Bachelor's degree and two years of experience. Must have one year of experience in the following skills: (1) building statistical models and machine learning models using large datasets from multiple resources; (2) building complex data analyses by leveraging scripting languages including Python, Java, or related scripting language; and (3) communicating with users, technical teams, and management to collect requirements, evaluate alternatives, and develop processes and tools to support the organization.
What you'd do
- 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 he… 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.
Tasks you're prepared for
(15 of 16 for Data Scientists)
- Analyze, manipulate, or process large sets of data using statistical software.
-
Apply feature selection algorithms to models predicting outcomes of interest, such as sales, attrition, and healthcare use.
via CSCD 484
- Apply sampling techniques to determine groups to be surveyed or use complete enumeration methods.
- Clean and manipulate raw data using statistical software.
- Compare models using statistical performance metrics, such as loss functions or proportion of explained variance.
+10 more covered tasks
Tasks you'd need to develop
(1)
Recommend data-driven solutions to key stakeholders.
These could be filled by an applied project, elective, or internship — see the program page for examples.
15/16
tasks
Data Scientist III - AMZ9442729
Amazon
Seattle, WA
2026-05-23
Description MULTIPLE POSITIONS AVAILABLE Employer: AMAZON.COM SERVICES LLC Offered Position: Data Scientist III Job Location: Seattle, Washington Job Number: AMZ9442729 Position Responsibilities: Own the data science elements of various products to help with data-based decision making,
Requirements
- Bachelor's degree or foreign equivalent degree in Statistics, Applied Mathematics, Economics, Engineering, Computer Science or a related field and two years of experience in the job offered or a relat… Bachelor's degree or foreign equivalent degree in Statistics, Applied Mathematics, Economics, Engineering, Computer Science or a related field and two years of experience in the job offered or a related occupation. Employer will accept four years of experience as equivalent to the Bachelor's degree and two years of experience. Must have one year of experience in the following skills: (1) building statistical models and machine learning models using large datasets from multiple resources; (2) building complex data analyses by leveraging scripting languages including Python, Java, or related scripting language; and (3) communicating with users, technical teams, and management to collect requirements, evaluate alternatives, and develop processes and tools to support the organization.
What you'd do
- 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 he… 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.
Nice to have
- Please see job description and the position requirements above.
Tasks you're prepared for
(15 of 16 for Data Scientists)
- Analyze, manipulate, or process large sets of data using statistical software.
-
Apply feature selection algorithms to models predicting outcomes of interest, such as sales, attrition, and healthcare use.
via CSCD 484
- Apply sampling techniques to determine groups to be surveyed or use complete enumeration methods.
- Clean and manipulate raw data using statistical software.
- Compare models using statistical performance metrics, such as loss functions or proportion of explained variance.
+10 more covered tasks
Tasks you'd need to develop
(1)
Recommend data-driven solutions to key stakeholders.
These could be filled by an applied project, elective, or internship — see the program page for examples.
15/16
tasks
Data Scientist III
Indeed
Seattle, WA
2026-05-23
Our Mission As the world's number 1 job site*, our mission is to help people get jobs. We strive to cultivate an inclusive and accessible workplace where all people feel comfortable being themselves. We're looking to grow our teams with more people who share our enthusiasm for innovation and c
What you'd do
- As a Data Scientist III at Indeed, you will leverage your expertise in data science, statistics, AI and machine learning to take on complex product, marketing and business challenges. You will design … As a Data Scientist III at Indeed, you will leverage your expertise in data science, statistics, AI and machine learning to take on complex product, marketing and business challenges. You will design and implement analytical solutions that guide decisions, optimize product performance or marketing campaigns, and create measurable impact across the organization.
- You will work closely with engineering and product or marketing teams to identify opportunities, evaluate initiatives, and develop models and analyses that inform data-driven strategies. You will also… You will work closely with engineering and product or marketing teams to identify opportunities, evaluate initiatives, and develop models and analyses that inform data-driven strategies. You will also contribute to building best practices in data science and mentor others in the team, helping elevate the technical capabilities and impact of those around you.
- Oversee the design and execution of advanced analyses, experiments, and machine learning models to address complex questions.
- Translate data into actionable insights to guide product, marketing and business decisions.
Tasks you're prepared for
(15 of 16 for Data Scientists)
- Analyze, manipulate, or process large sets of data using statistical software.
-
Apply feature selection algorithms to models predicting outcomes of interest, such as sales, attrition, and healthcare use.
via CSCD 484
- Apply sampling techniques to determine groups to be surveyed or use complete enumeration methods.
- Clean and manipulate raw data using statistical software.
- Compare models using statistical performance metrics, such as loss functions or proportion of explained variance.
+10 more covered tasks
Tasks you'd need to develop
(1)
Recommend data-driven solutions to key stakeholders.
These could be filled by an applied project, elective, or internship — see the program page for examples.
15/16
tasks
Data Scientist
Actalent
Seattle, WA
2026-05-23
Job Title: Data Scientist - Life Sciences LaboratoryJob Description This role combines hands-on laboratory science with advanced data science to support cutting-edge research in molecular biology, microbiology, and biochemistry. The Data Scientist - Life Sciences Laboratory executes end-to-end lab
Requirements
- Hands-on expertise with cutting-edge molecular biology, microbiology, and/or biochemistry methods and concepts.
- Familiarity with data analysis tools and methodologies commonly used in modern laboratory data analysis.
- 5+ years of experience as a data scientist or in a similar role involving data extraction, analysis, statistical modeling, and communication.
- 5+ years of experience with data querying languages such as SQL.
What you'd do
- Execute existing laboratory workflows from experimental planning through data analysis, ensuring accuracy, reproducibility, and timely completion of work.
- Recognize, document, and escalate protocol deviations to relevant stakeholders, and contribute to corrective and preventive actions.
- Ensure laboratory equipment and instruments remain in good operating condition, identify malfunctions, and perform or coordinate troubleshooting as needed.
- Maintain an up-to-date understanding of laboratory methods, protocols, and analytical techniques used in the lab.
Nice to have
- PhD degree in a life science discipline such as Biochemistry, Genetics, Molecular Biology, or Microbiology, with 8-10 years of directly related commercial experience.
- Ability to work effectively within multidisciplinary teams at the interface of life science and computer science.
- Broad familiarity with different areas of the life sciences and their experimental approaches.
- Hands-on experience in high-throughput research, including operation of liquid handling systems.
Tasks you're prepared for
(15 of 16 for Data Scientists)
- Analyze, manipulate, or process large sets of data using statistical software.
-
Apply feature selection algorithms to models predicting outcomes of interest, such as sales, attrition, and healthcare use.
via CSCD 484
- Apply sampling techniques to determine groups to be surveyed or use complete enumeration methods.
- Clean and manipulate raw data using statistical software.
- Compare models using statistical performance metrics, such as loss functions or proportion of explained variance.
+10 more covered tasks
Tasks you'd need to develop
(1)
Recommend data-driven solutions to key stakeholders.
These could be filled by an applied project, elective, or internship — see the program page for examples.
15/16
tasks
AI/ML Engineer - Higher Ed
Cengage Group
Portland, OR
2026-05-22
We believe in the power and joy of learning At Cengage, our employees have a direct impact in helping students around the world discover the power and joy of learning. We are bonded by our shared purpose - driving innovation that helps millions of learners improve their lives and achieve their
Requirements
- Bachelor's degree in Computer Science, Engineering, or related field
- 4+ years of experience in software engineering, with at least 2 years focused on AI/ML
- Strong proficiency in Python with experience building production ML or LLM systems
- Hands-on experience with modern AI APIs (OpenAI, Anthropic, AWS Bedrock)
What you'd do
- *HED AI Feature Development
- Ship and improve AI features weekly across Cengage HED platforms
- Build and integrate Student Assistant capabilities including tutoring, hinting, and feedback
- Develop Instructor Insight Assistant features for course analytics and at-risk student identification
Nice to have
- Experience in EdTech or adjacent domains with production education AI features
- Familiarity with agentic AI frameworks (LangChain, LlamaIndex, CrewAI)
- Background in learning science, educational psychology, or instructional design
- Experience with FERPA compliance and education-industry data handling
Tasks you're prepared for
(15 of 16 for Data Scientists)
- Analyze, manipulate, or process large sets of data using statistical software.
-
Apply feature selection algorithms to models predicting outcomes of interest, such as sales, attrition, and healthcare use.
via CSCD 484
- Apply sampling techniques to determine groups to be surveyed or use complete enumeration methods.
- Clean and manipulate raw data using statistical software.
- Compare models using statistical performance metrics, such as loss functions or proportion of explained variance.
+10 more covered tasks
Tasks you'd need to develop
(1)
Recommend data-driven solutions to key stakeholders.
These could be filled by an applied project, elective, or internship — see the program page for examples.
15/16
tasks
AI/ML Engineer - Higher Ed
Cengage Group
Boise, ID
2026-05-22
We believe in the power and joy of learning At Cengage, our employees have a direct impact in helping students around the world discover the power and joy of learning. We are bonded by our shared purpose - driving innovation that helps millions of learners improve their lives and achieve their
Requirements
- Bachelor's degree in Computer Science, Engineering, or related field
- 4+ years of experience in software engineering, with at least 2 years focused on AI/ML
- Strong proficiency in Python with experience building production ML or LLM systems
- Hands-on experience with modern AI APIs (OpenAI, Anthropic, AWS Bedrock)
What you'd do
- *HED AI Feature Development
- Ship and improve AI features weekly across Cengage HED platforms
- Build and integrate Student Assistant capabilities including tutoring, hinting, and feedback
- Develop Instructor Insight Assistant features for course analytics and at-risk student identification
Nice to have
- Experience in EdTech or adjacent domains with production education AI features
- Familiarity with agentic AI frameworks (LangChain, LlamaIndex, CrewAI)
- Background in learning science, educational psychology, or instructional design
- Experience with FERPA compliance and education-industry data handling
Tasks you're prepared for
(15 of 16 for Data Scientists)
- Analyze, manipulate, or process large sets of data using statistical software.
-
Apply feature selection algorithms to models predicting outcomes of interest, such as sales, attrition, and healthcare use.
via CSCD 484
- Apply sampling techniques to determine groups to be surveyed or use complete enumeration methods.
- Clean and manipulate raw data using statistical software.
- Compare models using statistical performance metrics, such as loss functions or proportion of explained variance.
+10 more covered tasks
Tasks you'd need to develop
(1)
Recommend data-driven solutions to key stakeholders.
These could be filled by an applied project, elective, or internship — see the program page for examples.
15/16
tasks
Machine Learning Engineer
Zoom
Seattle, WA
2026-05-22
Immigration sponsorship is not available for this position 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 enginee
What you'd do
- 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.
Tasks you're prepared for
(15 of 16 for Data Scientists)
- Analyze, manipulate, or process large sets of data using statistical software.
-
Apply feature selection algorithms to models predicting outcomes of interest, such as sales, attrition, and healthcare use.
via CSCD 484
- Apply sampling techniques to determine groups to be surveyed or use complete enumeration methods.
- Clean and manipulate raw data using statistical software.
- Compare models using statistical performance metrics, such as loss functions or proportion of explained variance.
+10 more covered tasks
Tasks you'd need to develop
(1)
Recommend data-driven solutions to key stakeholders.
These could be filled by an applied project, elective, or internship — see the program page for examples.
15/16
tasks
Data Scientists - Finance
T-Mobile USA, Inc.
Bellevue, WA
2026-05-22
Tasks you're prepared for
(15 of 16 for Data Scientists)
- Analyze, manipulate, or process large sets of data using statistical software.
-
Apply feature selection algorithms to models predicting outcomes of interest, such as sales, attrition, and healthcare use.
via CSCD 484
- Apply sampling techniques to determine groups to be surveyed or use complete enumeration methods.
- Clean and manipulate raw data using statistical software.
- Compare models using statistical performance metrics, such as loss functions or proportion of explained variance.
+10 more covered tasks
Tasks you'd need to develop
(1)
Recommend data-driven solutions to key stakeholders.
These could be filled by an applied project, elective, or internship — see the program page for examples.
15/16
tasks
Data Scientist - 3035128
Apex Systems, Inc.
Redmond, WA
2026-05-22
Tasks you're prepared for
(15 of 16 for Data Scientists)
- Analyze, manipulate, or process large sets of data using statistical software.
-
Apply feature selection algorithms to models predicting outcomes of interest, such as sales, attrition, and healthcare use.
via CSCD 484
- Apply sampling techniques to determine groups to be surveyed or use complete enumeration methods.
- Clean and manipulate raw data using statistical software.
- Compare models using statistical performance metrics, such as loss functions or proportion of explained variance.
+10 more covered tasks
Tasks you'd need to develop
(1)
Recommend data-driven solutions to key stakeholders.
These could be filled by an applied project, elective, or internship — see the program page for examples.
15/16
tasks
Data Scientist
ManpowerGroup
Redmond, WA
2026-05-22
Tasks you're prepared for
(15 of 16 for Data Scientists)
- Analyze, manipulate, or process large sets of data using statistical software.
-
Apply feature selection algorithms to models predicting outcomes of interest, such as sales, attrition, and healthcare use.
via CSCD 484
- Apply sampling techniques to determine groups to be surveyed or use complete enumeration methods.
- Clean and manipulate raw data using statistical software.
- Compare models using statistical performance metrics, such as loss functions or proportion of explained variance.
+10 more covered tasks
Tasks you'd need to develop
(1)
Recommend data-driven solutions to key stakeholders.
These could be filled by an applied project, elective, or internship — see the program page for examples.
15/16
tasks
AI/ML Engineer - Higher Ed
Cengage Group
Seattle, WA
2026-05-22
We believe in the power and joy of learning At Cengage, our employees have a direct impact in helping students around the world discover the power and joy of learning. We are bonded by our shared purpose - driving innovation that helps millions of learners improve their lives and achieve their
Requirements
- Bachelor's degree in Computer Science, Engineering, or related field
- 4+ years of experience in software engineering, with at least 2 years focused on AI/ML
- Strong proficiency in Python with experience building production ML or LLM systems
- Hands-on experience with modern AI APIs (OpenAI, Anthropic, AWS Bedrock)
What you'd do
- *HED AI Feature Development
- Ship and improve AI features weekly across Cengage HED platforms
- Build and integrate Student Assistant capabilities including tutoring, hinting, and feedback
- Develop Instructor Insight Assistant features for course analytics and at-risk student identification
Nice to have
- Experience in EdTech or adjacent domains with production education AI features
- Familiarity with agentic AI frameworks (LangChain, LlamaIndex, CrewAI)
- Background in learning science, educational psychology, or instructional design
- Experience with FERPA compliance and education-industry data handling
Tasks you're prepared for
(15 of 16 for Data Scientists)
- Analyze, manipulate, or process large sets of data using statistical software.
-
Apply feature selection algorithms to models predicting outcomes of interest, such as sales, attrition, and healthcare use.
via CSCD 484
- Apply sampling techniques to determine groups to be surveyed or use complete enumeration methods.
- Clean and manipulate raw data using statistical software.
- Compare models using statistical performance metrics, such as loss functions or proportion of explained variance.
+10 more covered tasks
Tasks you'd need to develop
(1)
Recommend data-driven solutions to key stakeholders.
These could be filled by an applied project, elective, or internship — see the program page for examples.
15/16
tasks
Machine Learning Engineer, Foundation Model Services
Apple
Seattle, WA
2026-05-21
Tasks you're prepared for
(15 of 16 for Data Scientists)
- Analyze, manipulate, or process large sets of data using statistical software.
-
Apply feature selection algorithms to models predicting outcomes of interest, such as sales, attrition, and healthcare use.
via CSCD 484
- Apply sampling techniques to determine groups to be surveyed or use complete enumeration methods.
- Clean and manipulate raw data using statistical software.
- Compare models using statistical performance metrics, such as loss functions or proportion of explained variance.
+10 more covered tasks
Tasks you'd need to develop
(1)
Recommend data-driven solutions to key stakeholders.
These could be filled by an applied project, elective, or internship — see the program page for examples.
15/16
tasks
Machine Learning Engineer - LLM Evaluation & Automation
TEKsystems
Seattle, WA
2026-05-21
Overview: We are seeking a Machine Learning Engineer to join a high-impact team focused on advancing LLM evaluation, NLP, and AI-driven automation. This role centers on designing scalable evaluation frameworks, optimizing prompt strategies, and building systems that ensure high-quality, consistent
Requirements
- 5+ years of experience in ML engineering, NLP, or AI/ML automation
- Strong programming skills in Python and SQL
- Deep understanding of machine learning concepts with a focus on NLP and advanced LLM capabilities (e.g., Chain-of-Thought, agentic workflows)
- Experience working with large-scale datasets and data pipelines
What you'd do
- Design and build LLM-based evaluation frameworks, including automated scoring pipelines and rubric-based grading systems
- Build and maintain data pipelines for evaluation datasets using Python, SQL, and scalable processing tools
- Translate complex evaluation results into clear, actionable insights for technical and non-technical stakeholders
- Implement automation workflows and agentic evaluation systems to improve efficiency and reduce manual efforts
Nice to have
- Experience with LLM-as-judge systems or human + model evaluation frameworks
- Background in inter-rater reliability, evaluation calibration, or judged systems design
- Experience with PySpark or distributed data processing tools
- Exposure to building dashboards or visualization tools for model performance tracking
Tasks you're prepared for
(15 of 16 for Data Scientists)
- Analyze, manipulate, or process large sets of data using statistical software.
-
Apply feature selection algorithms to models predicting outcomes of interest, such as sales, attrition, and healthcare use.
via CSCD 484
- Apply sampling techniques to determine groups to be surveyed or use complete enumeration methods.
- Clean and manipulate raw data using statistical software.
- Compare models using statistical performance metrics, such as loss functions or proportion of explained variance.
+10 more covered tasks
Tasks you'd need to develop
(1)
Recommend data-driven solutions to key stakeholders.
These could be filled by an applied project, elective, or internship — see the program page for examples.
15/16
tasks
Data Scientist
TEKsystems
Seattle, WA
2026-05-21
Overview We are seeking a Data Scientist to join a high-impact team focused on using data to inform product decisions and improve customer experience at scale. This role centers on experimentation, causal analysis, and predictive modeling, partnering closely with product and engineering teams to u
Requirements
- 3-5+ years of data science or analytics experience
- Strong SQL and Python skills
- Experience with experimentation (A/B testing), hypothesis testing, or causal analysis
- Experience working with data pipelines and large-scale datasets
What you'd do
- Design and analyze experiments (A/B testing) to evaluate product features
- Build and maintain data pipelines to support experimentation, analytics, and scalable product insights
- Develop predictive models to understand user behavior and system performance
- Translate data findings into actionable insights that directly influence product and engineering decisions
Nice to have
- Forecasting or time series experience
- Product analytics or customer behavior analysis
- Experience with cloud or modern data tools (e.g., Snowflake, Databricks)
- Exposure to NLP, LLMs, or unstructured data analysis
Tasks you're prepared for
(15 of 16 for Data Scientists)
- Analyze, manipulate, or process large sets of data using statistical software.
-
Apply feature selection algorithms to models predicting outcomes of interest, such as sales, attrition, and healthcare use.
via CSCD 484
- Apply sampling techniques to determine groups to be surveyed or use complete enumeration methods.
- Clean and manipulate raw data using statistical software.
- Compare models using statistical performance metrics, such as loss functions or proportion of explained variance.
+10 more covered tasks
Tasks you'd need to develop
(1)
Recommend data-driven solutions to key stakeholders.
These could be filled by an applied project, elective, or internship — see the program page for examples.
15/16
tasks
Data Scientist, Manufacturing Analytics
Ford Motor Company
Salem, OR
2026-05-21
We made history and now we work to transform the future - for our customers, our communities and our families. You'll see your work on the road every day, helping people move freely and pursue their dreams. At Ford, you can build more than vehicles. Come build what matters. Do you believe data tel
What you'd do
- Accelerate the application of value-added analytics and machine learning into the portfolio of products for Manufacturing Analytics.
- Drive analytic excellence into product teams by collaborating with Data Scientists, Data Engineers and Software Engineers in analytic and machine learning methods.
- Work closely with the Product Manager and Product Owner to translate Business Value needs into analytic deliverables and, where appropriate, software products for delivery by product teams.
- Work hands-on with the team and other partners to deliver solutions that meet our customer's requirements and needs.
Tasks you're prepared for
(15 of 16 for Data Scientists)
- Analyze, manipulate, or process large sets of data using statistical software.
-
Apply feature selection algorithms to models predicting outcomes of interest, such as sales, attrition, and healthcare use.
via CSCD 484
- Apply sampling techniques to determine groups to be surveyed or use complete enumeration methods.
- Clean and manipulate raw data using statistical software.
- Compare models using statistical performance metrics, such as loss functions or proportion of explained variance.
+10 more covered tasks
Tasks you'd need to develop
(1)
Recommend data-driven solutions to key stakeholders.
These could be filled by an applied project, elective, or internship — see the program page for examples.
15/16
tasks
Data Scientist, Manufacturing Analytics
Ford Motor Company
Olympia, WA
2026-05-21
We made history and now we work to transform the future - for our customers, our communities and our families. You'll see your work on the road every day, helping people move freely and pursue their dreams. At Ford, you can build more than vehicles. Come build what matters. Do you believe data tel
What you'd do
- Accelerate the application of value-added analytics and machine learning into the portfolio of products for Manufacturing Analytics.
- Drive analytic excellence into product teams by collaborating with Data Scientists, Data Engineers and Software Engineers in analytic and machine learning methods.
- Work closely with the Product Manager and Product Owner to translate Business Value needs into analytic deliverables and, where appropriate, software products for delivery by product teams.
- Work hands-on with the team and other partners to deliver solutions that meet our customer's requirements and needs.
Tasks you're prepared for
(15 of 16 for Data Scientists)
- Analyze, manipulate, or process large sets of data using statistical software.
-
Apply feature selection algorithms to models predicting outcomes of interest, such as sales, attrition, and healthcare use.
via CSCD 484
- Apply sampling techniques to determine groups to be surveyed or use complete enumeration methods.
- Clean and manipulate raw data using statistical software.
- Compare models using statistical performance metrics, such as loss functions or proportion of explained variance.
+10 more covered tasks
Tasks you'd need to develop
(1)
Recommend data-driven solutions to key stakeholders.
These could be filled by an applied project, elective, or internship — see the program page for examples.
15/16
tasks
Machine Learning Platform Engineer, Apple Services Engineering
Apple
Seattle, WA
2026-05-20
Role Number: 200664012-3337 Summary We're building the evaluation platform that will serve all of Apple's generative AI and agent systems. Evaluating non-deterministic AI systems is one of the hardest unsolved problems in production ML - and one Apple has to get right at scale. We're bu
Requirements
- 4-8 years of software engineering experience building and shipping production services.
- Strong Python. You're fluent with FastAPI, Pydantic, and the modern Python ecosystem. You write code that's clean, tested, and easy for the next person to pick up.
- Builder's mindset. You enjoy shipping. You're comfortable iterating quickly on scoped problems and knowing when to slow down for the parts that need it.
- Fluency with AI coding tools. You actively use tools like Claude Code (or equivalents) in your day-to-day workflow, including features like skills, slash commands, and agent-style workflows. You have … Fluency with AI coding tools. You actively use tools like Claude Code (or equivalents) in your day-to-day workflow, including features like skills, slash commands, and agent-style workflows. You have a good intuition for when to lean on them, when to steer them, and how to get high-quality output.
What you'd do
- We're building the evaluation platform that will serve all of Apple's generative AI and agent systems. Evaluating non-deterministic AI systems is one of the hardest unsolved problems in production ML … We're building the evaluation platform that will serve all of Apple's generative AI and agent systems. Evaluating non-deterministic AI systems is one of the hardest unsolved problems in production ML - and one Apple has to get right at scale. We're building the platform that makes it tractable for every team here.
- This is a hands-on engineering role with a lot of autonomy. You'll write a lot of Python and own meaningful pieces of the platform end-to-end. You'll be partnering closely with research engineers, mod… This is a hands-on engineering role with a lot of autonomy. You'll write a lot of Python and own meaningful pieces of the platform end-to-end. You'll be partnering closely with research engineers, model and serving teams, product and feature teams, and the infra and data platform groups this work integrates with.
- Build and ship: Take ownership of features and services within the evaluation platform: APIs, SDKs, orchestration components, evaluation runners. You'll have the room to make calls on your own work an… Build and ship: Take ownership of features and services within the evaluation platform: APIs, SDKs, orchestration components, evaluation runners. You'll have the room to make calls on your own work and the support to deliver it well.
- Productionize ML research: Partner with research engineers to take their prototype code and turn it into reliable services. You'll learn their world quickly and translate research patterns into clean … Productionize ML research: Partner with research engineers to take their prototype code and turn it into reliable services. You'll learn their world quickly and translate research patterns into clean Python that holds up under real load.
Nice to have
- Experience working on developer platforms, internal tools, or SDKs
- Production experience with LLM/agent systems - building, evaluating, or operating them
- Familiarity with job orchestration frameworks (Temporal.io, Airflow, or similar)
- Distributed compute experience (Ray, Dask, or Kubernetes-based job systems)
Tasks you're prepared for
(15 of 16 for Data Scientists)
- Analyze, manipulate, or process large sets of data using statistical software.
-
Apply feature selection algorithms to models predicting outcomes of interest, such as sales, attrition, and healthcare use.
via CSCD 484
- Apply sampling techniques to determine groups to be surveyed or use complete enumeration methods.
- Clean and manipulate raw data using statistical software.
- Compare models using statistical performance metrics, such as loss functions or proportion of explained variance.
+10 more covered tasks
Tasks you'd need to develop
(1)
Recommend data-driven solutions to key stakeholders.
These could be filled by an applied project, elective, or internship — see the program page for examples.
15/16
tasks
Data Scientist III
Chewy Inc.
Bellevue, WA
2026-05-20
Data Scientist III (Chewy, Inc.; Bellevue, Washington): Develop machine learning infrastructure and data pipelines that improve data quality. Use machine learning frameworks in both development, testing, and production environments to create and deploy new technologies. Identify opportunities fo
Requirements
- At least one data science subject area (e.g., casual inference, NLP, forecasting, etc.);
- R, PySpark, Spark, Scala, Java, PyTorch, TensorFlow, Docker;
- Object-oriented programming with Python; and
- Data visualization tools and packages (Tableau or similar).
Tasks you're prepared for
(15 of 16 for Data Scientists)
- Analyze, manipulate, or process large sets of data using statistical software.
-
Apply feature selection algorithms to models predicting outcomes of interest, such as sales, attrition, and healthcare use.
via CSCD 484
- Apply sampling techniques to determine groups to be surveyed or use complete enumeration methods.
- Clean and manipulate raw data using statistical software.
- Compare models using statistical performance metrics, such as loss functions or proportion of explained variance.
+10 more covered tasks
Tasks you'd need to develop
(1)
Recommend data-driven solutions to key stakeholders.
These could be filled by an applied project, elective, or internship — see the program page for examples.