Senior Data Scientist, Growth

Job description

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: 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, and Applied AI (Post Sales). 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. You will: • Define and evolve Glean’s growth measurement framework across acquisition, activation, engagement, retention, resurrection, and expansion, including metrics such as WAU, activation, engagement intensity, retention, and feature adoption • Build and analyze end-to-end user and account growth funnels to understand where users experience value, where they drop off, and which behaviors are most predictive of durable engagement • Diagnose adoption gaps and develop bottoms-up growth strategies for high-impact enterprise accounts, identifying where product, deployment, engagement, or organizational barriers are limiting growth and partnering with Applied AI and R&D leaders on targeted interventions. • Identify and size high-leverage growth opportunities across onboarding, product discoverability, education, lifecycle messaging, collaboration and virality, and new product surfaces • Partner across R&D and Applied AI to turn product capabilities and behavioral insights into scalable adoption plays, identifying the customers and user populations best suited for new experiences and translating those opportunities into targeted field interventions. • Partner closely with Product, Design, and Engineering to translate product ideas into testable hypotheses, well-defined success metrics, instrumentation plans, and decision criteria • Design and analyze rigorous A/B tests, phased rollouts, and quasi-experiments; use causal evidence to recommend whether products should launch, iterate, or change direction • Develop behavioral and needs-based user segments and translate those insights into targeted product interventions • Inform roadmap and investment decisions by quantifying reachable populations, expected impact, confidence, dependencies, and tradeoffs before significant development begins • Build trusted, reusable growth datasets, dashboards, and self-serve analytical tools that allow Product and Engineering partners to independently understand product health and investigate changes • Lead cross-functional data science projects end-to-end, translating ambiguous product questions into clear insights, recommendations, and decisions for audiences ranging from engineers to executives Example areas of focus could include improving new-user onboarding and activation, converting occasional users into habitual users, increasing adoption of emerging AI experiences, optimizing high-traffic entry surfaces, improving feature discovery, developing lifecycle strategies, and building account-level adoption frameworks for enterprise customers, and translating new product capabilities into scalable Applied AI adoption motions. You are: • 7+ years of experience in a highly quantitative data science, product analytics, or growth analytics role, with a degree in Statistics, Mathematics, Computer Science, or a related field • Demonstrated experience partnering with Product and Engineering teams to identify opportunities and influence product roadmap decisions • Strong grounding in statistics, experimentation, causal inference, statistical power, segmentation, funnel analysis, and retention analysis • Exceptionally high AI proficiency through habitual, high-value use of LLMs, with sound judgment ab