XBOX Growth Intelligence is seeking a Senior Data Scientist, Product Analytics to partner directly with Product, Engineering, and cross-functional leaders to shape the future of XBOX product experiences. This role will drive product strategy and execution through data, helping teams understand player behavior, identify growth opportunities, measure business impact, and accelerate decision-making. The Senior Data Scientist helps product teams consistently use data to prioritize investments, translating insights into measurable improvements in areas such as DAU, retention, and engagement, and becoming a trusted strategic analytics partner to Product and Business leaders. The ideal candidate combines strong analytical rigor, product intuition, and the ability to influence leaders through actionable insights.
Responsibilities
Lead ecosystem-level analyses across XBOX experiences. Inform and influence high-stake C-level investment decisions through data-driven insights.
Apply econometric, statistical, and causal inference methods to evaluate growth and optimization opportunities on audience reach, engagement and monetization.
Design, build and evaluate experiments and incrementality measurement frameworks and models to validate hypotheses and measure investment ROI.
Leverage agentic AI tools to create reusable analytical assets and self-service capabilities.
Mentor team members and raise the analytical bar across the organization.
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:
- Expertise in SQL, Python or R and agentic AI tools.
- Extensive experience in experimentation, causal inference, forecasting, and machine-learning modeling in general.
- Executive communication skills to translate ambiguous business questions or technical details into structured analyses and actionable recommendations.
- Ability to influence senior stakeholders decisions through data-driven recommendations.
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, read more about requesting accommodations.
Skills Required
- Doctorate in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or a related field plus at least 1 year of data science experience, or equivalent experience
- Master's degree in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or a related field plus at least 3 years of data science experience, or equivalent experience
- Bachelor's degree in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or a related field plus at least 5 years of data science experience, or equivalent experience
- Expertise in SQL, Python or R, and agentic AI tools
- Extensive experience in experimentation, causal inference, forecasting, and machine-learning modeling
- Executive communication skills to translate ambiguous business questions or technical details into structured analyses and actionable recommendations
- Ability to influence senior stakeholder decisions through data-driven recommendations
Microsoft Compensation & Benefits Highlights
The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about Microsoft and has not been reviewed or approved by Microsoft.
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Fair & Transparent Compensation — Pay is presented as broadly competitive overall, with clear role/level/location variation and an emphasis on using posted ranges and band information for apples-to-apples comparisons.
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Retirement Support — Retirement benefits are described as a standout, highlighted by a strong 401(k) match structure and immediate vesting, plus additional plan features for tax-advantaged saving.
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Parental & Family Support — Family-oriented benefits are portrayed as a meaningful strength, with substantial paid parental leave and added supports like back-up care and adoption/surrogacy assistance.
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