Description
- 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
- 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 about when and how to apply them, rigorous validation, and continuous workflow improvement
- Experience designing and analyzing product experiments and communicating causal findings in a way that drives clear product decisions
- Strong proficiency in SQL and practical fluency in a statistical programming language such as Python or R
- Experience building durable analytical datasets, metrics, dashboards, and data models rather than relying primarily on ad hoc analysis. dbt experience is a plus.
- A strong product and business mindset, with 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
- You have experience in B2B SaaS, especially enterprise AI, or have worked on products where adoption occurs across both users and accounts
- You have experience partnering with GTM or Post-Sales teams and are comfortable using data to challenge assumptions, shape account strategy, and drive impact through action.
- You have a track record of identifying growth opportunities from behavioral data and turning them into shipped, measurable product interventions
- You have helped build experimentation or product-measurement capabilities that increased the velocity and quality of decision-making for an organization
- You combine strong quantitative rigor with product intuition and are comfortable making recommendations in highly ambiguous problem spaces
- You have a very strong sense of ownership and self-motivation. You are laser-focused on delivering business impact while growing as an individual along with Glean
- You are good at managing evolving priorities while successfully delivering core initiatives
- This role is hybrid (4 days a week in our Mountain View office)
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