WHY WE'RE LOOKING FOR YOU
Retool is rapidly growing, and we’re tackling increasingly complex questions about our customers, product, and business. We’re looking for a Data Scientist to join our Data Science & Analytics team to help Retool make better, faster decisions at scale.
This is a generalist role for someone who’s excited by ambiguity, motivated by impact, and comfortable partnering across teams to shape strategy—not just report on outcomes. You’ll focus on understanding why things are happening, what signals matter most, and what Retool should do next, with success measured by real business and customer impact. Your work will inform company‑wide decisions across Product, GTM, and Leadership.
WHAT YOU'LL DO
- 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
WHO YOU'LL WORK WITH
Data science and analytics is a centralized, company‑level function that partners closely across teams at Retool.
- Product and Engineering to inform product direction, roadmap, and prioritization
- GTM teams, such as Marketing, Sales, Customer Success, and RevOps, to understand acquisition, expansion, and retention dynamics
- Executive leadership—supporting strategic decisions across the company with clear, customer‑grounded insights
THE SKILLSET YOU'LL BRING
We’re looking for someone who’s comfortable operating in fast‑moving, evolving environments, is comfortable making progress with imperfect information, and who enjoys owning problems end‑to‑end.
- 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