New 
Principal Data Scientist - CoreAI
 Microsoft | |
 United States, Washington, Redmond | |
 Jul 08, 2025 | |
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OverviewAt CoreAI, we empower developers and organizations to shape the future with Artificial Intelligence (AI). Our Growth and Data Science team in Microsoft's Developer Division accelerates this mission by delivering insights, models, and tools that guide product strategy and unlock growth across our developer ecosystem. We're looking for Principal Data Scientists with a track record of delivering product wins at global scale, elevating data cultures, and thriving in ambiguous, fast-evolving environments. In this role, you will measure what matters, surface actionable insights, run rigorous experiments, and deliver AI capabilities that developers love and enterprises trust. Join us for a front-row seat to AI transformation and innovation at Microsoft scale. Your work will directly impact tens of millions of developers globally - including 95% of the Fortune 500 -- across products like GitHub Copilot, the Visual Studio family of editors, Azure developer experiences, and next-generation coding agents. Ready to define the future of developer productivity with data and AI? We'd love to hear from you. 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.
ResponsibilitiesCreate customer and business impact by identifying and leading high-leverage data science and analytics opportunities across product areas Shape organizational strategy, technical direction, and multi-million dollar investments through end-to-end project leadership, blending strategic influence with deep technical execution Drive alignment across executives and diverse stakeholders through trusted partnerships and compelling communication Establish and operationalize metrics, experimentation frameworks, and causal inference approaches tailored to dynamic AI systems and enterprise contexts Advance and scale data, analytics, experimentation, and machine learning infrastructure and self-serve tools to empower thousands of colleagues to make smarter, faster decisions Mentor other data scientists and champion best practices to uplift our craft and collaborative culture Leverage AI to accelerate workflows and amplify team productivity | |