SlipstreamJobs tracks this role from the company's public career site. Apply directly on the employer's site.
Glean is a Work AI platform that helps enterprises leverage AI for intelligent search, AI assistants, and scalable AI agents. The company has built an Enterprise Graph and Personal Knowledge Graph that powers deeply personalized, context-aware responses across organizations. Recognized as one of Fast Company's World's Most Innovative Companies (Top 10, 2025), CNBC's Disruptor 50, and Gartner's Tech Innovators in Agentic AI, Glean serves 1,000+ employees across 50+ industries in 25+ countries.
As Senior Data Scientist for Growth, you will be the quantitative partner to Growth Product, Engineering, Design, and Product Marketing teams. Your primary focus is accelerating user adoption, engagement, and sustained product usage through data-driven insights and experimentation.
Key responsibilities include:
- Define and evolve Glean's growth measurement framework across the full user lifecycle: acquisition, activation, engagement, retention, resurrection, and expansion. Own core metrics including WAU (weekly active users), activation rates, engagement intensity, retention cohorts, and feature adoption.
- Build and analyze end-to-end user and account funnels to identify value realization points, drop-off moments, and behavioral predictors of durable engagement.
- Identify and size high-leverage growth opportunities across onboarding, product discoverability, education, lifecycle messaging, collaboration and virality mechanics, and new product surfaces.
- Partner with Product, Design, and Engineering to translate product ideas into testable hypotheses, define clear success metrics, plan instrumentation, and establish decision criteria.
- Design and analyze experiments to validate growth bets, measure impact, and drive rapid learning cycles.
- Use behavioral data and cohort analysis to uncover where Glean can create substantially more value for users and drive expansion within existing accounts.
You will work in a world-class data organization spanning data science, applied science, data engineering, and business analytics, with the opportunity to shape how enterprises adopt and scale AI across their workforce.
