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 ability to work with messy, early-stage data and turn it into clear, actionable insights
- End-to-end ownership: from problem framing to delivery, you drive work independently
- Clear communicator across technical and non-technical audiences
- B2B SaaS experience, ideally in enterprise AI
- You are excited about improving internal tooling/processes in Data Science teams to make others more productive, e.g. improve AI adoption, improve A/B testing tooling etc.
Location:
- This role is hybrid (4 days a week in one of our Bay Area offices)
Compensation & Benefits:
The standard base salary range for this position is $175,000 - $240,000 annually. Compensation offered will be determined by factors such as location, level, job-related knowledge, skills, and experience. Certain roles may be eligible for variable compensation, equity, and benefits.
We offer a comprehensive benefits package including competitive compensation, Medical, Vision, and Dental coverage, generous time-off policy, and the opportunity to contribute to your 401k plan to support your long-term goals. When you join, you'll receive a home office improvement stipend, as well as an annual education and wellness stipends to support your growth and wellbeing. We foster a vibrant company culture through regular events, and provide healthy lunches daily to keep you fueled and focused.
We are a diverse bunch of people and we want to continue to attract and retain a diverse range of people into our organization. We're committed to an inclusive and diverse company. We do not discriminate based on gender, ethnicity, sexual orientation, religion, civil or family status, age, disability, or race.
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