Senior Data Scientist - Ecosystem Economics & Growth, XBOX

Overview

Are you passionate about using data, economics, and advanced analytics to influence strategy at scale? The XBOX Growth Intelligence team is seeking a Senior Data Scientist to drive ecosystem growth decisions across XBOX, Game Pass, Console, PC, and Store experiences. The Senior Data Scientist enables XBOX leadership to make materially better portfolio, product, content, and investment decisions, establishing trusted frameworks for measuring ecosystem health across XBOX and its partners, and creating reusable analytical products and self-service capabilities that accelerate decision-making and reduce one-off analysis

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 Masters 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 Bachelors 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.

• 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 stakeholders decisions through data-driven recommendations.

#GamingJobs

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.