
Hover or tap a row for full statistics (EUR / month on this chart).
Salary analysis
Compared with the selected benchmark ("Market Average: Senior Level"), this listing's salary midpoint is about 187% higher. The offer sits above the benchmark range (€4,350–€9,000). The listed pay band (€16,667–€21,667) is tighter than the benchmark, which suggests lower salary variability. This benchmark is based on 18 comparable listings.
| Market | Lower bound (25th percentile) | Median | Upper bound (75th percentile) |
|---|---|---|---|
| Market Average: Data Scientist | €3,250/per month | €5,775/per month | €8,681/per month |
Growth Data Scientist focused on accelerating user adoption, engagement, and sustained product usage within the Growth and Enterprise Readiness Data Science team. This role sits within the Growth Data Science group and partners with Growth Product, Engineering, Design, and Product Marketing. You’ll turn ambiguous growth opportunities into measurable product bets, build measurement and experimentation systems, and use behavioral data to identify where Glean can create value. You will: Define and evolve 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. Identify opportunities across onboarding, product discoverability, education, lifecycle messaging, virality, and new product surfaces. Partner with Product, Design, and Engineering to turn ideas into testable hypotheses and instrumentation plans. Design and analyze A/B tests and quasi-experiments. Develop behavioral segments and translate insights into targeted interventions. Inform roadmap and investment decisions with quantitative estimates. Build reusable growth datasets, dashboards, and self-serve analytics tools. Lead cross-functional data science projects end-to-end. Example areas include onboarding, activation, adoption of AI experiences, and account-level adoption frameworks for enterprise customers.
Job Details
Responsibilities
- Define and evolve 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
- Identify opportunities across onboarding, product discoverability, education, lifecycle messaging, virality, and new product surfaces
- Partner with Product, Design, and Engineering to turn ideas into testable hypotheses and instrumentation plans
- Design and analyze A/B tests and quasi-experiments
- Develop behavioral segments and translate insights into targeted interventions
- Inform roadmap and investment decisions with quantitative estimates
- Build reusable growth datasets, dashboards, and self-serve analytics tools
- Lead cross-functional data science projects end-to-end
Requirements
- 7+ years of experience in quantitative data science, product analytics, or growth analytics
- degree in Statistics, Mathematics, Computer Science, or related field
- SQL proficiency and Python or R
- experience building analytical datasets and dashboards
- ability to collaborate with product and engineering teams
Skills & Technologies
Education Level
MastersBenefits & Perks
Recruitment Process
- 1Screening
- 2First interview
- 3Technical interview
- 4Offer

| Location | Active listings |
|---|---|
| Remote - Global | 1 |
| San Francisco, CA | 1 |
| Role type | Active listings |
|---|---|
| Cloud Infrastructure Engineer | 1 |
| Role level | Active listings |
|---|---|
| Mid-Level | 1 |
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