Senior Data Scientist, Core Product

Glean•San Francisco, CA

11h•Hybrid

About The Position

Glean is building a world-class data organization across data science, applied science, data engineering, and business analytics. This role sits within the Core Product Data Science team in R&D and is based in the Bay Area (San Francisco or South Bay). Data scientists at Glean partner closely with engineering, product, and design to: Define and build core data assets (KPIs, pipelines, dashboards) to measure AI product performance Improve product telemetry and logging to enable robust analysis Develop scalable data models and self-serve analytics tools for cross-functional teams Establish strong measurement foundations and identify opportunities to improve key metrics Influence product roadmaps through data-driven insights Build quantitative frameworks to rigorously evaluate product performance and product-market fit The role focuses on advancing the Glean Assistant experience, including: Improving analytics around user engagement and value Evolving Glean Chat from information delivery to co-performing with users Expanding use cases across document creation, data analysis, and software engineering Supporting new contexts (e.g., meetings) and modalities (e.g., voice, image generation) Enabling more collaborative, multi-user experiences

Requirements

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 proficiency in SQL and Python; experience with modern data stacks (e.g., dbt, analytics engineering pipelines)
Experience working with complex, early-stage datasets and translating them into actionable insights
Strong product and business mindset, with experience defining KPIs, guardrails, and dashboards that drive decisions
Solid foundation in statistics, including experimentation and causal inference methods
Ability to independently own projects end-to-end, from problem framing to delivery
Clear communicator, able to explain complex analyses to both technical and non-technical audiences

Nice To Haves

Experience in B2B SaaS, particularly enterprise AI
Strong ownership mindset with a focus on delivering business impact
Ability to manage shifting priorities while executing on core initiatives
Experience collaborating across time zones
Proficiency using AI tools in day-to-day workflows
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.

Responsibilities

Define and build core data assets (KPIs, pipelines, dashboards) to measure AI product performance
Improve product telemetry and logging to enable robust analysis
Develop scalable data models and self-serve analytics tools for cross-functional teams
Establish strong measurement foundations and identify opportunities to improve key metrics
Influence product roadmaps through data-driven insights
Build quantitative frameworks to rigorously evaluate product performance and product-market fit
Improving analytics around user engagement and value
Evolving Glean Chat from information delivery to co-performing with users
Expanding use cases across document creation, data analysis, and software engineering
Supporting new contexts (e.g., meetings) and modalities (e.g., voice, image generation)
Enabling more collaborative, multi-user experiences