Senior Data Scientist Growth
Glean is an enterprise AI platform that connects company knowledge and systems to provide permission-aware search, AI assistance, and agents.
Funding history
About Glean
Glean develops enterprise Work AI software. Its platform provides enterprise search, a conversational AI assistant, and tools to build, govern, and orchestrate AI agents using a company’s connected data and permissions.
Skills
Candidate Availability
Required and preferred rules are kept separate and reflect the wording in the original posting.
About the Role
You will develop growth measurement frameworks, analyze user and account funnels, and identify adoption gaps and high-impact opportunities. You will design and analyze experiments, develop user segments, quantify roadmap decisions, and build reusable datasets, dashboards, and analytical tools. You will translate ambiguous product questions into recommendations for technical and non-technical stakeholders.
Requirements
- 7+ years of quantitative data science, product analytics, or growth analytics experience
- Statistics, experimentation, causal inference, statistical power, segmentation, funnel analysis, and retention analysis knowledge
- LLM proficiency
- Product experiment design and causal analysis experience
- SQL proficiency
- Python or R fluency
- Experience building analytical datasets, metrics, dashboards, and data models
- KPI and measurement framework experience
- Communication skills for technical and non-technical audiences
Responsibilities
- Define and evolve growth measurement frameworks across acquisition, activation, engagement, retention, resurrection, and expansion
- Build and analyze user and account growth funnels
- Diagnose adoption gaps and develop growth strategies for enterprise accounts
- Identify and size growth opportunities across onboarding, discoverability, education, lifecycle messaging, collaboration, virality, and product surfaces
- Translate product ideas into testable hypotheses, success metrics, instrumentation plans, and decision criteria
- Design and analyze A/B tests, phased rollouts, and quasi-experiments
- Develop behavioral and needs-based user segments
- Quantify populations, impact, confidence, dependencies, and tradeoffs for roadmap decisions
- Build reusable growth datasets, dashboards, and self-serve analytical tools
- Lead cross-functional data science projects end-to-end
Benefits
- Medical coverage
- Vision coverage
- Dental coverage
- Generous time-off policy
- 401k plan
- Home office improvement stipend
- Annual education stipend
- Annual wellness stipend
- Regular events
- Daily healthy lunches
Hiring Process
Brief AI-focused exercise or discussion during the interview process.
