Data Scientist
Data Scientist analyzes customer behavior, product usage, and business performance to drive strategic decisions across Product, GTM, and leadership. Requires 5+ years in data science/product analytics, strong SQL, and experience in high-growth B2B SaaS environments.
About the job
Responsibilities
- Analyze customer behavior, product usage, and business performance to surface insights tied to core metrics like ARR, retention, and sales efficiency.
- Frame ambiguous business questions into clear analytical approaches and recommendations.
- Build models, frameworks, and narratives that influence strategy, prioritization, and tradeoffs.
- Identify customer friction and risk early—and help teams act before issues escalate.
- Enable teams to self-serve on foundational analytics so you can stay focused on higher-impact work.
Requirements
- 5+ years of experience working in data science and/or product analytics.
- Experience working in startup or high-growth environments, especially B2B SaaS.
- Strong SQL proficiency with an eye for writing performant, robust queries.
- Comfort operating in ambiguity and proactively identifying and defining business problems.
- Experience helping teams shift from intuition-driven to data-informed decision-making.
- Exposure to experimentation, forecasting, or predictive modeling.
- Experience designing data models and building pipelines to unblock yourself.
- Strong ability to synthesize complex information (data, context, and constraints) into clear, concise narratives for business stakeholders.
- Comfort moving quickly by default to produce actionable insights—and slowing down when the cost of a wrong decision is high.
- Ease context-switching across problem areas and teams, from high-level strategy to low-level details as needed.
Compensation
- Base pay range: $182,800 – $250,000 per year.
- Additional compensation in the form(s) of equity and/or commission are dependent on the position offered.
- Retool provides a comprehensive benefit plan, including medical, dental, vision, and 401(k).
Skills
SQL, Python, Data Modeling, Pipelines, Experimentation, Forecasting, Predictive Modeling, Product Analytics
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