Senior Data Scientist

Microsoft•Redmond, WA

About The Position

Why Xbox Planning & Insights The Xbox Planning & Insights team plays a central role in shaping the strategic direction of the Gaming organization by delivering business intelligence, analytics, and decision science that drive impact across the Xbox ecosystem. We partner cross-functionally to optimize performance, inform investment decisions, and ensure alignment with long-term goals. Whether supporting Game Pass content strategy, membership planning, or platform insights, our work is grounded in a customer centric approach and a commitment to execution excellence—from idea to measurable outcomes. We’re looking for candidates who are comfortable navigating evolving or complex challenges, bring thoughtful and data-driven decision-making, and are passionate about building the future of gaming. 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. Why join us You won’t just be analyzing data—you’ll be shaping how millions of gamers experience Xbox. From product insights to strategic planning, your work will directly influence the future of Xbox.

Requirements

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.
Having a growth mindset: Demonstrates a growth mindset through adaptability, curiosity, and continuous learning
Being proactive: Anticipate questions, propose analyses, and independently push work to completion in ambiguous spaces.
Data‑driven and governance‑minded: Ensure accuracy, consistency, and compliance of data sources; contribute to improving data pipelines and governance practices.
Embody our Culture & Values

Nice To Haves

Proficiency in SQL and at least one programming language (Python or R).
Understanding of statistical methods, experimentation design, and causal inference.
Proven ability to synthesize complex data into clear, actionable insights.
Demonstrated ability to connect data science work to business strategy—not just what happened, but why and what to do next.
Proficiency with cloud data platforms (e.g., Azure Data Lake, Synapse, Databricks) and distributed data processing.
Background in product analytics, consumer subscriptions, or gaming (or similar digital ecosystems).
Familiarity with data privacy regulations (GDPR, CCPA) and governance frameworks.
Experience building scalable analytics solutions, reusable frameworks, or automation for recurring insights.
Experience deploying models to production and measuring real-world impact.

Responsibilities

Transform data into decisions: Apply statistical, machine learning, and predictive modeling techniques to large, complex datasets to uncover opportunities, risks, and tradeoffs for product and business.
Develop and deploy data science solutions: Build scalable models and algorithms for player segmentation, personalization, forecasting, and optimization.
Tell a compelling data story: Create executive-ready reports, dashboards, and presentations that clearly communicate insights, implications, and recommendations. Present findings with clarity, tailoring the message to both technical and non-technical audiences.
Drive alignment: Partner with engineering, product, and business stakeholders to define success metrics, align on KPIs, and drive clarity in decision-making. Experienced in cross-functional teamwork to land decisions with clarity and follow-through.
Measure impact: Closely partner with the Product and Experimentation team to design and evaluate hypothesis-driven A/B tests and other experiments; ensure methodological rigor and interpret results for business impact.
Advance data science best practices: Contribute to improving data pipelines, governance, and experimentation frameworks. Mentor junior team members and champion a culture of innovation and learning.

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