Senior Data Scientist, Growth

About this role

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, 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.

You will:

• Define and evolve Glean’s growth measurement framework across acquisition, activation, engagement, retention, resurrection, and expansion. Own core metrics such as WAU, activation, engagement intensity, retention, and feature adoption.

• Build and analyze end-to-end user and account funnels to identify where users realize value, where they drop off, and which behaviors predict durable engagement.

• Identify and size high-leverage opportunities across onboarding, product discoverability, education, lifecycle messaging, collaboration and virality, and new product surfaces.

• Partner with Product, Design, and Engineering to turn product ideas into testable hypotheses, clear success metrics, instrumentation plans, and decision criteria.

• Design and analyze A/B tests, phased rollouts, and quasi-experiments. Apply causal inference to recommend whether products should launch, iterate, or change direction.

• Develop behavioral and needs-based segments and translate 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, metrics, and self-serve analytical tools so Product and Engineering can independently understand product health and investigate changes.

• Lead cross-functional data science projects end-to-end—from ambiguous product questions to clear insights, recommendations, and decisions for audiences ranging from engineers to executives.

Example areas of focus 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.

About you:

• 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.

• Experience building durable analytical datasets, metrics, dashboards, and data models—not relying primarily on ad hoc analysis. dbt experience is a plus.

• 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 analys

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