New 
Data Scientist
 Microsoft | |
 United States, Washington, Redmond | |
 Oct 26, 2025 | |
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OverviewThe Digital Direct Sales (DDS) team at Microsoft is a global eCommerce organization that helps consumers and very small businesses discover, learn, and buy Microsoft products. Operating in over 120 countries, DDS combines data-driven insights, experimentation, and personalization to deliver intelligent, adaptive shopping experiences. We engage customers throughout their digital journeys, driving emotional connection, business growth, and innovation at scale. We are seeking a highly skilled and strategic Data Scientist to join our Reporting, Analytics, and Data Science (RAD) team. As a Data Scientist in the RAD team, you'll operate at the forefront of AI innovation-working fast to uncover meaningful applications that drive impact across the business. You'll harness emerging technologies to solve complex problems, accelerate experimentation, and deliver scalable, intelligent solutions that shape the future of analytics at Microsoft. This opportunity will allow you to:Accelerate your career growth by leading high-visibility AI initiatives Deepen your experience in cutting-edge data science and machine learning techniques Influence how Microsoft applies AI to unlock new business value Microsoft's mission is to empower every person and every organization on the planet to achieve more. 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.In alignment with our Microsoft values, we are committed to cultivating an inclusive work environment for all employees to positively impact our culture every day.
ResponsibilitiesData Preparation & Exploration: Acquire, clean, and organize datasets; query and visualize data; explore key attributes to support analysis and experiments Model Development & Evaluation: Apply appropriate modeling techniques, build and refine Retrieval-Augmented Generation (RAG)/Large Language Models (LLM), and evaluate results for statistical and business significance Performance & Integration: Optimize model accuracy, scalability, and efficiency while embedding solutions into business workflows and tools Research & Innovation: Stay current with industry trends, emerging AI/Machine Learning (ML) techniques, and best practices; contribute to thought leadership and experimentation Customer & Business Alignment: Understand customer goals, identify growth opportunities, and manage expectations to ensure project outcomes deliver valueCollaboration & Technical Execution: Partner across teams, write efficient/debuggable code, and contribute domain experience to align initiatives with business strategyOther: Embody our Culture and Values | |