Senior Data Scientist, Growth
Senior data scientist partnering with Growth Product, Engineering, and Applied AI to improve enterprise user adoption, engagement, retention, and expansion. The role requires 7+ years of quantitative experience, strong experimentation and causal inference skills, and proficiency in SQL plus Python or R.
About the job
Responsibilities
- Define and evolve growth measurement frameworks across acquisition, activation, engagement, retention, resurrection, and expansion.
- Build and analyze end-to-end user and account growth funnels to identify value realization, drop-off points, and behaviors predictive of durable engagement.
- Diagnose adoption gaps and develop growth strategies for high-impact enterprise accounts.
- Identify and size growth opportunities across onboarding, discoverability, education, lifecycle messaging, collaboration, virality, and new product surfaces.
- Partner with Product, Design, Engineering, Applied AI, and Post-Sales teams to turn behavioral insights into adoption initiatives and testable product hypotheses.
- Design and analyze A/B tests, phased rollouts, and quasi-experiments; apply causal evidence to product decisions.
- Develop behavioral and needs-based user segments and targeted interventions.
- Inform roadmap and investment decisions by quantifying reach, impact, confidence, dependencies, and tradeoffs.
- Build reusable growth datasets, dashboards, metrics, and self-service analytical tools.
- Lead cross-functional data science projects from problem framing through recommendations and follow-through.
Requirements
- 7+ years of experience in quantitative data science, product analytics, or growth analytics.
- Degree in Statistics, Mathematics, Computer Science, or a related field.
- Experience partnering with Product and Engineering teams and influencing roadmap decisions.
- Strong knowledge of statistics, experimentation, causal inference, statistical power, segmentation, funnel analysis, and retention analysis.
- Strong proficiency in SQL and practical fluency in Python or R.
- Experience building durable analytical datasets, metrics, dashboards, and data models.
- Experience designing and analyzing product experiments and communicating causal findings.
- Experience defining KPIs, guardrail metrics, and measurement frameworks.
- Ability to own complex projects end-to-end and communicate quantitative findings to technical and non-technical audiences.
- High proficiency using LLMs with rigorous validation and sound judgment.
Nice-to-haves
- Experience with dbt.
- B2B SaaS experience, especially enterprise AI or products with user- and account-level adoption.
- Experience partnering with GTM or Post-Sales teams.
- Experience building experimentation or product-measurement capabilities.
- Strong product intuition and experience working in ambiguous problem spaces.
Compensation
- Compensation details were not provided.
Skills
SQL, Python, R, dbt, A/B Testing, Causal Inference, Statistics, Product Analytics, Growth Analytics, Funnel Analysis, Retention Analysis, Segmentation, Data Modeling, LLMs, Dashboards
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