Senior Data Scientist, Growth
Mountain View, CA Hybrid
$200,000–$260,000 a yearJobFig found this opening at its original source and checks that it remains available.
About the role
Glean is building a world-class data organization spanning data science, applied science, data engineering, and business analytics. This role sits within the Growth and Enterprise Readiness Data Science team, with a primary focus on accelerating user adoption, engagement, and sustained product usage. As a Growth Data Scientist, you will be the quantitative partner to Growth Product, Engineering, Design, and Product Marketing. You’ll turn ambiguous growth opportunities into measurable product bets, build the measurement and experimentation systems that allow us to learn quickly, and use behavioral data to identify where Glean can create substantially more value for its users.
What you'll bring
- 7+ years of experience in quantitative data science, product analytics, or growth analytics, plus a degree in Statistics, Mathematics, Computer Science, or a related field.
- Strong grounding in statistics, experimentation, causal inference, statistical power, segmentation, funnel analysis, and retention analysis.
- Demonstrated experience designing and analyzing product experiments and translating causal findings into clear product decisions.
- Strong proficiency in SQL and practical fluency in Python or R.
- Demonstrated ability to partner with Product and Engineering teams to identify opportunities and influence roadmap decisions.
- Exceptionally high AI proficiency through habitual, high-value use of LLMs, with sound judgment about when and how to apply them, rigorous validation, and continuous workflow improvement.
- A strong product and business mindset, including experience defining KPIs, guardrail metrics, and measurement frameworks that influence decisions.
- Ability to independently own complex projects end-to-end, from problem framing and measurement through analysis, recommendation, and follow-through.
- Clear, concise communication skills, with the ability to explain complex quantitative findings to both technical and non-technical audiences.
- Feel free to reference any tools, platforms, or workflows you use today — prior Glean experience isn't required.
- Experience building durable analytical datasets, metrics, dashboards, and data models—not relying primarily on ad hoc analysis. dbt experience is a plus.