Principal Data Scientist

Microsoft•Redmond, WA

3d•Hybrid

About The Position

Microsoft AI (MAI) creates innovative AI-powered and personalized web experiences in Microsoft Windows, Edge & Bing, that inform, entertain, add value, save money, and breathe productivity into the life and work of millions of customers. MAI makes the web work for our consumers, advertisers, and publishers in a safe environment where everyone can get informed, entertained, save money and thrive! MSN is a personalized content feed powering user experiences across Microsoft. Our mission is to empower every person on the planet to be informed, entertained, and inspired. We are looking for an experienced Principal Data Scientist to join our Growth and Analytics team. 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.

Requirements

Doctorate 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 Master's Degree in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field AND 7+ 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 10+ years data science experience (e.g., managing structured and unstructured data, applying statistical techniques and reporting results)
OR equivalent experience.

Nice To Haves

Doctorate 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 Master's Degree in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field AND 10+ 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 12+ years data-science experience (e.g., managing structured and unstructured data, applying statistical techniques and reporting results)
OR equivalent experience.
7+ years of experience in data science, statistical modeling, business analytics, forecasting, or data-driven strategy.
Experience in product, web, and/or content analytics, with the ability to connect user behavior to business outcomes.
Solid communication and storytelling skills, with the ability to translate complex analyses into clear business recommendations.
Proven ability to manage stakeholders, prioritize effectively, and deliver actionable, data-driven insights.
Experience working with large-scale event-level data and transforming raw data into metrics, dashboards, and analytical solutions using PySpark, Scala, or similar tools.
Familiarity with content ecosystems, advertising, online shopping metrics, and the key drivers of engagement and monetization.

Responsibilities

Partner with stakeholders as a trusted thought partner to drive data-informed business decisions and strategic planning.
Collaborate with cross-functional teams to define features, estimate initiative impact, and support engagement and revenue growth through analytics.
Build forecasting solutions and time-series models to project engagement, traffic, and revenue, and support scenario planning.
Analyze large-scale data to identify trends, user behavior patterns, and content performance insights that improve product quality and recommendations.
Develop dashboards, reporting tools, and automated monitoring to track business health and compare actual performance against forecast.
Build metric frameworks to detect anomalies, diagnose root causes, and provide timely insights when key business metrics shift.
Conduct business modeling to identify growth opportunities, evaluate trade-offs, and prioritize initiatives with solid long-term ROI.
Design and analyze A/B tests to measure incremental impact, evaluate algorithm changes, and guide iterative improvements.
Apply predictive modeling, time-series analysis, and experimentation methods to improve forecasting accuracy and business performance.
Communicate insights, forecasts, and recommendations clearly to technical and non-technical stakeholders to support informed decision-making.