Senior Data Scientist, Core Product

About Glean:   Glean is the Work AI platform that helps everyone work smarter with AI. What began as the industry’s most advanced enterprise search has evolved into a full-scale Work AI ecosystem, powering intelligent Search, an AI Assistant, and scalable AI agents on one secure, open platform. With over 100 enterprise SaaS connectors, flexible LLM choice, and robust APIs, Glean gives organizations the infrastructure to govern, scale, and customize AI across their entire business - without vendor lock-in or costly implementation cycles.   At its core, Glean is redefining how enterprises find, use, and act on knowledge. Its Enterprise Graph and Personal Knowledge Graph map the relationships between people, content, and activity, delivering deeply personalized, context-aware responses for every employee. This foundation powers Glean’s agentic capabilities - AI agents that automate real work across teams by accessing the industry’s broadest range of data: enterprise and world, structured and unstructured, historical and real-time. The result: measurable business impact through faster onboarding, hours of productivity gained each week, and smarter, safer decisions at every level.   Recognized by Fast Company as one of the World’s Most Innovative Companies (Top 10, 2025), by CNBC’s Disruptor 50, Bloomberg’s AI Startups to Watch (2026), Forbes AI 50, and Gartner’s Tech Innovators in Agentic AI, Glean continues to accelerate its global impact. With customers across 50+ industries and 1,000+ employees in more than 25 countries, we’re helping the world’s largest organizations make every employee AI-fluent, and turning the superintelligent enterprise from concept into reality.   If you’re excited to shape how the world works, you’ll help build systems used daily across Microsoft Teams, Zoom, ServiceNow, Zendesk, GitHub, and many more - deeply embedded where people get things done. You’ll ship agentic capabilities on an open, extensible stack, with the craft and care required for enterprise trust, as we bring Work AI to every employee, in every company.

About the Role

This role sits on the Core Product Data Science team within R&D, part of a world-class organization spanning data science, applied science, data engineering, and analytics. Based in the Bay Area (San Francisco or South Bay), you'll be embedded at the center of where enterprise AI is heading.

You Will:

You'll partner with Engineering, Product, and Design to own measurement, insight, and impact across the Glean Assistant — one of the most interesting product surfaces in enterprise AI today:

• Define what "good" looks like for AI — build the KPIs, pipelines, and dashboards that let the team move with conviction; lead logging improvements that turn nascent telemetry into a reliable foundation for decision-making
• Redefine user engagement for an AI-first product — measuring value when AI is doing half the work is an unsolved problem; you'll be on the frontier of figuring it out
• Scale analytics access — develop data models and self-serve tools so cross-functional partners can move fast from a shared, accurate source of truth — without a bottleneck
• Shape what gets built — identify what's working, what isn't, and why; influence roadmaps with quantitative frameworks and rigorous assessments of product-market fit
• Work on surfaces that are moving fast — Glean Chat evolving from informing users to co-performing complex work alongside them; new job types (document generation, data analysis, software engineering), new settings (meetings), new modalities (voice, image), and multi-user experiences

This is a rare opportunity to do foundational data science work on AI products that are actually deployed at scale inside real organizations — not a research prototype, not a side bet. If you want to work at the center of where enterprise AI is heading, this is the role.

About you:

• 6+ years of experience in a quantitative data science role (3+ years with a PhD) in Statistics, Mathematics, Computer Science, or a related field
• Strong SQL and Python skills; comfortable with modern data stacks (dbt, analytics engineering pipelines)
• Fluent in AI tools as part of your everyday workflow
• Product and business mindset — you know how to define KPIs, set guardrails, and build dashboards that actually drive decisions
• Solid statistics foundation, including experimentation and causal inference
• Proven