New 
Principal Data Scientist
 Microsoft | |
 United States, Washington, Redmond | |
 Oct 19, 2025 | |
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OverviewThe Outlook Data and AI Platform team is seeking a Principal Data Science Leader to shape our data strategy, drive innovation, and build the data culture that powers Copilot and AI transformation at scale. This leader will be responsible for advancing our data science capabilities, defining product analytics best practices, and creating the data flywheel that accelerates impact across engineering, product, and customer experiences. As a Principal Data Scientist, you will partner with executives, product teams, and engineers to define the future of Outlook data and AI. You will be expected to provide strategic guidance, lead large-scale initiatives, and mentor peers while translating data insights into measurable business and product 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.
ResponsibilitiesDefine and execute a long-term vision for data science, analytics, and evaluation frameworks.Shape the data flywheel by creating scalable measurement and feedback loops that continuously improve product performance and user experience.Influence product and business strategy by synthesizing data, insights, and emerging research into actionable recommendations for senior leadership.Lead large-scale, cross-functional programs for data-driven evaluation, experiment pipelines, and automated measurement systems.Build, scale, and promote a culture of data-informed decision making across engineering, product, and business teams.Manage, coach and mentor data scientists and analysts, fostering excellence in experimentation, analytics, and business impact.Design and implement advanced statistical and machine learning methods to measure product effectiveness and uncover actionable insights.Establish and champion product analytics best practices (e.g., metric design, funnel analysis, experiment setup, and decision frameworks).Lead the design, execution, and analysis of A/B tests and other controlled experiments.Drive acquisition, management, and analysis of large-scale datasets to inform engineering and product innovation.Partner with engineers, designer, user researchers, and product managers to align data initiatives with product roadmaps and customer needs.Ensure seamless integration of evaluation and analytics into product workflows, from design through deployment.Serve as a trusted thought leader to executive stakeholders, communicating complex findings in a clear, actionable way. | |