Data Scientist Jobs in Washington
Data Scientist jobs in Washington are among the most active in the country, concentrated in technology, cloud computing, healthcare, and aerospace, with openings at every level from entry-level analyst to principal scientist. Seattle leads hiring, followed by Redmond and Bellevue, where anchor employers like Microsoft, Amazon, and Boeing maintain large data science teams. Machine learning engineering, natural language processing, and health informatics are the most in-demand specialties across Washington's market. Find a role that fits below and apply directly.
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Showing 5 of 110+ Data Scientist jobs
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.
We are seeking a Senior Data Scientist to lead end-to-end yield optimization initiatives for Azure infrastructure (e.g., virtual machines, storage). In this role, you will frame ambiguous business problems, translate revenue, hardware, and capacity data into actionable insights, and guide decisions that balance resource utilization, cost efficiency, and customer experience. You will apply analytics, machine learning, causal inference, and visualization to recommend strategies, influence cross-functional decisions, and measure business outcomes. Your work will inform decisions like how we price new products, how we use prices to encourage certain customer behaviors, what promotions we create, etc.
Microsoft’s mission is to empower every person and every organization on the planet to achieve more. As employees we come together with a growth mindset, innovate to empower others, and collaborate to realize our shared goals. Each day we build on our values of respect, integrity, and accountability to create a culture of inclusion where everyone can thrive at work and beyond.
Responsibilities
Data Analysis
- Write efficient, readable code in Python, SQL, KQL, or similar languages to prepare and analyze large-scale revenue, hardware, and capacity datasets, leveraging distributed data-processing systems to identify pricing and yield opportunities.
Modeling & Yield Optimization
- Select, develop, and validate appropriate statistical and machine-learning approaches for resource allocation and pricing, assessing methodological limitations and both statistical and business significance.
Cross-Functional Collaboration
- Partner with business planning, engineering, product management, and finance teams to define objectives, prioritize analytical work, and align yield strategies with business goals.
- Influence decisions through evidence, communicate trade-offs, and drive alignment on success measures and implementation.
Experimentation & A/B Testing
- Own experiment design and impact measurement for optimization hypotheses, including success metrics, guardrails, and interpretation of results.
- Build causal inference models (e.g., difference-in-differences, synthetic control) when randomized experiments are not feasible.
- Estimate demand elasticity and customer substitution effects.
Insights & Decision Influence
- Develop decision-relevant metrics, dashboards, and compelling narratives that translate analyses into actionable recommendations.
- Present findings and analytical limitations to technical and executive audiences, build stakeholder support, and guide decisions on key yield initiatives.
Thought Leadership
- Stay current with industry trends in AI, cloud economics, and optimization techniques.
- Provide mentorship through code reviews, innovation, and sharing best practices.
Business Acumen
- Apply understanding of Azure pricing, cloud economics, and customer workflows to shape actionable recommendations and explain business trade-offs.
Embody our culture and values.
Qualifications
Required Qualifications
-
Doctorate in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field AND 1+ year(s) data-science experience (e.g., managing structured and unstructured data, applying statistical techniques and reporting results)
- OR Master's Degree in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field AND 3+ years data-science experience (e.g., managing structured and unstructured data, applying statistical techniques and reporting results)
- OR Bachelor's Degree in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field AND 5+ years data-science experience (e.g., managing structured and unstructured data, applying statistical techniques and reporting results)
- OR equivalent experience.
Preferred Qualifications
- Doctorate 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 Master's Degree in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field AND 6+ 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 8+ years data-science experience (e.g., managing structured and unstructured data, applying statistical techniques and reporting results)
- OR equivalent experience.
- Experience with yield or revenue management, pricing optimization, or cloud resource allocation.
Data Science IC4 - The typical base pay range for this role across the U.S. is USD $119,800 - $234,700 per year. There is a different range applicable to specific work locations, within the San Francisco Bay area and New York City metropolitan area, and the base pay range for this role in those locations is USD $160,200 - $261,000 per year.
Certain roles may be eligible for benefits and other compensation. Find additional benefits and pay information here:
https://careers.microsoft.com/us/en/us-corporate-pay
This position will be open for a minimum of 5 days, with applications accepted on an ongoing basis until the position is filled.
Microsoft is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to age, ancestry, citizenship, color, family or medical care leave, gender identity or expression, genetic information, immigration status, marital status, medical condition, national origin, physical or mental disability, political affiliation, protected veteran or military status, race, ethnicity, religion, sex (including pregnancy), sexual orientation, or any other characteristic protected by applicable local laws, regulations and ordinances. If you need assistance with religious accommodations and/or a reasonable accommodation due to a disability during the application process.
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.
We are seeking a Senior Data Scientist to lead end-to-end yield optimization initiatives for Azure infrastructure (e.g., virtual machines, storage). In this role, you will frame ambiguous business problems, translate revenue, hardware, and capacity data into actionable insights, and guide decisions that balance resource utilization, cost efficiency, and customer experience. You will apply analytics, machine learning, causal inference, and visualization to recommend strategies, influence cross-functional decisions, and measure business outcomes. Your work will inform decisions like how we price new products, how we use prices to encourage certain customer behaviors, what promotions we create, etc.
Microsoft’s mission is to empower every person and every organization on the planet to achieve more. As employees we come together with a growth mindset, innovate to empower others, and collaborate to realize our shared goals. Each day we build on our values of respect, integrity, and accountability to create a culture of inclusion where everyone can thrive at work and beyond.
Responsibilities
Data Analysis
- Write efficient, readable code in Python, SQL, KQL, or similar languages to prepare and analyze large-scale revenue, hardware, and capacity datasets, leveraging distributed data-processing systems to identify pricing and yield opportunities.
Modeling & Yield Optimization
- Select, develop, and validate appropriate statistical and machine-learning approaches for resource allocation and pricing, assessing methodological limitations and both statistical and business significance.
Cross-Functional Collaboration
- Partner with business planning, engineering, product management, and finance teams to define objectives, prioritize analytical work, and align yield strategies with business goals.
- Influence decisions through evidence, communicate trade-offs, and drive alignment on success measures and implementation.
Experimentation & A/B Testing
- Own experiment design and impact measurement for optimization hypotheses, including success metrics, guardrails, and interpretation of results.
- Build causal inference models (e.g., difference-in-differences, synthetic control) when randomized experiments are not feasible.
- Estimate demand elasticity and customer substitution effects.
Insights & Decision Influence
- Develop decision-relevant metrics, dashboards, and compelling narratives that translate analyses into actionable recommendations.
- Present findings and analytical limitations to technical and executive audiences, build stakeholder support, and guide decisions on key yield initiatives.
Thought Leadership
- Stay current with industry trends in AI, cloud economics, and optimization techniques.
- Provide mentorship through code reviews, innovation, and sharing best practices.
Business Acumen
- Apply understanding of Azure pricing, cloud economics, and customer workflows to shape actionable recommendations and explain business trade-offs.
Embody our culture and values.
Qualifications
Required Qualifications
-
Doctorate in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field AND 1+ year(s) data-science experience (e.g., managing structured and unstructured data, applying statistical techniques and reporting results)
- OR Master's Degree in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field AND 3+ years data-science experience (e.g., managing structured and unstructured data, applying statistical techniques and reporting results)
- OR Bachelor's Degree in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field AND 5+ years data-science experience (e.g., managing structured and unstructured data, applying statistical techniques and reporting results)
- OR equivalent experience.
Preferred Qualifications
- Doctorate 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 Master's Degree in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field AND 6+ 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 8+ years data-science experience (e.g., managing structured and unstructured data, applying statistical techniques and reporting results)
- OR equivalent experience.
- Experience with yield or revenue management, pricing optimization, or cloud resource allocation.
Data Science IC4 - The typical base pay range for this role across the U.S. is USD $119,800 - $234,700 per year. There is a different range applicable to specific work locations, within the San Francisco Bay area and New York City metropolitan area, and the base pay range for this role in those locations is USD $160,200 - $261,000 per year.
Certain roles may be eligible for benefits and other compensation. Find additional benefits and pay information here:
https://careers.microsoft.com/us/en/us-corporate-pay
This position will be open for a minimum of 5 days, with applications accepted on an ongoing basis until the position is filled.
Microsoft is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to age, ancestry, citizenship, color, family or medical care leave, gender identity or expression, genetic information, immigration status, marital status, medical condition, national origin, physical or mental disability, political affiliation, protected veteran or military status, race, ethnicity, religion, sex (including pregnancy), sexual orientation, or any other characteristic protected by applicable local laws, regulations and ordinances. If you need assistance with religious accommodations and/or a reasonable accommodation due to a disability during the application process.
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Find Data Scientist JobsData Scientist Jobs by City in Washington
Where Washington roles are concentrated, by current openings.
Data Scientist Job Market in Washington
A snapshot from current Washington openings, updated as new roles post.
Who's Hiring
- Amazon31
- TikTok7
- Walmart7
- Microsoft6
- Google4
Top Industries Hiring
- Technology & Software25
- Retail10
- E-Commerce & Online Marketplaces4
- Banking & Financial Services3
- Distribution & Wholesale2
What Washington Employers Look For
The qualifications that appear most often in data scientist jobs across Washington.
- Bachelor's or master's degree in statistics, computer science, mathematics, or a related field
- Proficiency in Python or R for data analysis, modeling, and automation
- Experience with machine learning frameworks such as TensorFlow, PyTorch, or scikit-learn
- Ability to query and manipulate large datasets using SQL or distributed computing tools like Spark
- Familiarity with cloud platforms including AWS, Azure, or Google Cloud for model deployment
- Strong communication skills for presenting findings to technical and non-technical stakeholders
Data Scientist Jobs in Washington: Frequently Asked Questions
How do you become a data scientist in Washington?
Data scientist roles in Washington do not require a state-issued license or registration. Most Washington employers expect at least a bachelor's degree in a quantitative field such as statistics, computer science, or applied mathematics, with a master's degree preferred for senior positions. Building a portfolio of applied projects, completing graduate coursework or bootcamps with industry partnerships, and gaining hands-on experience with cloud tools common in Washington's tech sector strengthens any application.
How much do data scientists make in Washington?
Data scientists in Washington earn a median of about $163,350 a year, based on May 2025 Bureau of Labor Statistics wage data, ranging from around $79,930 for the lowest 10% to over $220,040 for the top 10%. Pay rises with experience, specialty, and employer.
Which companies hire data scientists in Washington?
Employers hiring data scientists in Washington right now include Amazon, TikTok, and Walmart, based on current listings on Migrate Mate as of September 2026. Washington's concentration of technology headquarters, major healthcare systems, and aerospace manufacturers means demand for data scientists runs consistently across multiple industries throughout the year.
Which Washington cities have the most data scientist jobs?
Seattle, Bellevue, and Redmond have the most data scientist openings in Washington. Seattle drives the largest share of demand through its dense cluster of technology companies, life sciences firms, and enterprise software headquarters, while Redmond and Bellevue benefit directly from Microsoft's campus and the broader Eastside corridor of cloud and software employers.
Are there remote data scientist jobs in Washington?
Yes, and more than most fields. About 49% of data scientist openings tied to Washington are remote or hybrid as of September 2026, reflecting how naturally this role lends itself to distributed work. Modeling, analysis, and research tasks are the most commonly fully remote, while roles involving close collaboration with product or engineering teams tend to favor hybrid arrangements.
How can I get hired as a data scientist in Washington with little or no experience?
The most realistic entry path is applying to associate data scientist or data analyst roles, which large Washington employers like Microsoft, Amazon, and Providence Health use as pipelines into senior data science positions. University of Washington and Washington State University graduates benefit from formal new-grad programs and on-campus recruiting at these employers. Building a public project portfolio on GitHub, completing internships, and moving laterally from adjacent roles such as business intelligence analyst or data engineer significantly improves early-career candidacy.
Where can I find and apply to data scientist jobs in Washington?
You can find and apply to data scientist jobs in Washington on Migrate Mate, which lists current Washington openings across industries and experience levels. Find roles that fit your background and apply directly to each one.
See All 110+ Data Scientist Jobs in Washington
Find roles in Washington that match your experience and apply in just a few clicks.
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