New 
Principal Data Scientist
 Microsoft | |
 United States, Washington, Redmond | |
 Jul 13, 2025 | |
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OverviewWe are looking for a Principal Data Scientist to join the Power Apps Interface team - the team building the agentic platform at the heart of Microsoft's next-generation business applications. The future of software isn't just low-code - it's AI-first. It understands user intent and leverages generative code, autonomous agents, and intelligent UI. Power Apps is leading this transformation by reimagining app development as a workspace for human-agent collaboration where users co-create with copilots, delegate tasks to agents, and operate in a system of AI-infused experiences. Our mission is to empower everyone - from professional developers to domain experts - with the ability to craft powerful business solutions through conversational design, generative UX, and a team of powerful agents. From adaptive controls to end-to-end agent workflows, our team builds the platform capabilities that enable seamless interaction between humans and AI within business-critical environments. If you're passionate about redefining how people build software and want to shape the future of agent-based platforms and generative application development, this is the team for you. Join us and help build the intelligent core powering the next wave of enterprise innovation.
ResponsibilitiesAs a Principal Data Scientist, your core mission will be partnering with the wider team to make sure data, data science (DS), and artificial intelligence (AI) are used effectively, efficiently, and responsibly. We are looking for candidates who love answering questions using data. You will lead by example by applying AI, machine learning, and data science to further Copilot and agentic product enhancements. Additional responsibilities include: Working closely with a variety of teams like partner data science, engineering, and UX teams. Developing ML models and solutions using classical algorithms as well as foundation models. Deploying these solutions into production. Measuring and reporting success, using A/B and shadow experiments, creating dashboards and reports as necessary. Using data to answer business questions like potential impact and usage. Customer journey, NSAT, churn, retention analysis. Presentation of work in the team and at Microsoft, such as during Town Halls and MLADS. Supporting business impact and evaluation supported decision making culture. | |