Principal Data Scientist
 Microsoft | |
 United States, Washington, Redmond | |
 Oct 22, 2025 | |
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OverviewMicrosoft is a company where passionate innovators come to collaborate, envision what can be and take their careers further. This is a world of more possibilities, more innovation, more openness, and the sky is the limit thinking in a cloud-enabled world. Microsoft's Azure Data engineering team is leading the transformation of analytics in the world of data with products like databases, data integration, big data analytics, messaging & real-time analytics, and business intelligence. The products our portfolio include Microsoft Fabric, Azure SQL DB, Azure Cosmos DB, Azure PostgreSQL, Azure Data Factory, Azure Synapse Analytics, Azure Service Bus, Azure Event Grid, and Power BI. Our mission is tobuild the data platform for the age of AI, powering a new class of data-first applications and driving a data culture. The Fabric Real-Time Intelligence (RTI) Data Science team is hiring a Principal Data Scientist to drive productled growth across RealTime Intelligence. In this team, you'll partner closely with PM, Engineering, and Design to shape the usage funnel for RTI experiences (e.g., onramps, trials, and realtime workloads), build and productionize causal and predictive models, and run disciplined experimentation that improves acquisition, activation, engagement, retention, and conversion. What makes this team unique is our endtoend ownership: from telemetry quality and semantic modeling, to growth analytics and A/B testing, to shipping actionable signals back into the product (including anomaly detection and trial logic) so we can learn and iterate quickly at scale. As the Principal Data Scientist, you will set the technical bar for experimentation, causal inference, and business impact measurement, while coaching a highperforming vteam to translate insights into shipped growth features. We do not just value differences or different perspectives. We seek them out and invite them in so we can tap into the collective power of everyone in the company. As a result, our customers are better served.
ResponsibilitiesLead Product-Led Growth (PLG) strategy through data science: Define and execute the experimentation and modeling roadmap to improve acquisition, activation, engagement, retention, and monetization. Design and operationalize experiments: Build and scale A/B testing and causal inference frameworks to measure impact and guide product decisions. Develop predictive and causal models: Deliver models that forecast user behavior, identify growth opportunities, and inform product interventions.Partner crossfunctionally: Collaborate with Product, Engineering, and Design to translate insights into shipped features that accelerate growth. Elevate data quality and observability: Ensure telemetry, metrics, and pipelines enable trustworthy experimentation and decisionmaking. Influence longterm growth strategy: Provide thought leadership on PLG best practices and mentor peers to raise the bar for experimentation and analytics.Embody our culture and values | |