We are looking for a Senior Data & Applied Scientist to help teams make better product and business decisions through rigorous experimentation, solid statistical thinking, and practical use of AI in everyday analytical work.

This is a hands-on role for someone who enjoys learning, questioning assumptions, and applying data science to real-world decisions at scale. This is not a “reporting” role. It is a decision-making role, where experimentation, judgment, and AI-enabled workflows come together to shape real outcomes.

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.

Starting January 26, 2026, Microsoft AI (MAI) employees who live within a 50- mile commute of a designated Microsoft office in the U.S. or 25-mile commute of a non-U.S., country-specific location are expected to work from the office at least four days per week. This expectation is subject to local law and may vary by jurisdiction.

Responsibilities

• Experimentation & A/B Testing
• Design, analyze, and interpret A/B experiments end-to-end, from hypothesis formulation to final decision
• Choose appropriate metrics, success criteria, and evaluation windows based on user behavior and business context.
• Identify and diagnose common experimentation issues (e.g., bias, interference, power limitations, metric sensitivity).
• Communicate experimental results clearly, including uncertainty, limitations, and trade-offs.
• Decision Science & Insights
• Go beyond “did it move the metric?” to explain why results happened and what decision should be made
• Combine experimental evidence with observational analysis when appropriate
• Partner closely with product, engineering, and design stakeholders to influence direction using data
• AI-First Analytical Work
• Use AI tools to accelerate analysis, exploration, and insight generation (e.g., faster hypothesis testing, code generation, narrative summaries).
• Continuously evaluate where AI can improve experimentation workflows, without compromising rigor or correctness.
• Develop good judgment about when to rely on automation vs. when deep statistical reasoning is required.
• Learning & Craft Development
• Stay current on experimentation methods, causal inference, and applied statistics.
• Learn and adopt new tools, techniques, and best practices quickly.
• Contribute to shared standards and documentation that improve how teams run experiments and make decisions.

• 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., * 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.

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