Principal Data Scientist

Microsoft•Redmond, WA

7d•$142,800 - $304,200•Hybrid

About The Position

Microsoft AI (MAI) is building the next generation of AI-powered consumer experiences across Microsoft products, connecting people to information, entertainment, shopping, and productivity through intelligent, personalized experiences. MSN and Copilot Discover are at the center of this vision, helping millions of users discover relevant content, stay informed, and engage with the web in meaningful ways. The MSN & Copilot Discover Business Analytics team serves as a horizontal analytics team supporting multiple product, engineering, marketplace, monetization, and business teams across the ecosystem. We are responsible for driving business insights, forecasting, strategic planning, experimentation, monetization analytics, and decision-making frameworks that influence product investments and business outcomes at scale. We are seeking an experienced Principal Business Analytics Data Scientist with solid business acumen, deep analytical expertise, and experience in content platforms, digital advertising, and monetization. This role offers a unique opportunity to work at the intersection of user engagement, AI-powered content discovery, and revenue optimization while partnering closely with product teams, MAI Marketplace, Monetization, Finance, and Engineering organizations. The ideal candidate combines rigorous analytical thinking with a solid understanding of content ecosystems, advertising marketplaces, user engagement, forecasting, experimentation, and business strategy. They are comfortable navigating ambiguity, influencing senior stakeholders, and translating complex data into actionable business decisions. 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.
Experience in content ecosystems, news feeds, recommendation systems, search, shopping, or content discovery platforms.
Experience partnering with advertising, monetization, or marketplace organizations.
Familiarity with key engagement and monetization metrics such as sessions, time spent, retention, RPM, ad requests, inventory utilization, advertiser demand, and marketplace efficiency.
Experience leading analytics for large-scale consumer products with millions of users.
Demonstrated success influencing product strategy and business outcomes through data-driven insights.
Solid understanding of AI-powered consumer experiences and their impact on user engagement and monetization.
Experience managing cross-functional initiatives involving Product, Engineering, Monetization, Marketplace, and Finance stakeholders.

Responsibilities

Serve as a trusted analytics partner to leadership and cross-functional teams, translating data into clear business recommendations.
Partner with Product, Engineering, MAI Marketplace, Monetization, Finance, and Business Planning teams to shape strategy and investment decisions.
Analyze user engagement, content consumption, marketplace dynamics, and revenue performance to identify growth opportunities and business risks.
Develop business frameworks that connect product initiatives, user behavior, content quality, and monetization outcomes.
Build forecasting and scenario-planning models for engagement, traffic, ad requests, and revenue.
Leverage AI and machine learning solutions to automate business insights, improve forecasting accuracy, enhance decision-making processes, and scale analytical capabilities across the organization.
Evaluate tradeoffs between user experience, engagement, and monetization to support long-term business growth.
Communicate insights clearly to senior stakeholders and influence decisions through data-driven storytelling.