Senior Data Scientist
RundooAbout the role
About Rundoo ℹ️
Our mission is to empower independent supply stores with best-in-class technology. Think of your local hardware store or mom-and-pop nursery—these are our clients. From paint to lumber to flooring, over 200,000 such stores across the country sell over $1T of building materials annually using outdated, on-premises systems. We’re aiming to help them modernize so that they can continue to thrive.
Backed by leading investors including Bessemer and CRV, we've raised $18M across three rounds and are growing quickly. Our team is made up of builders, sellers, and industry veterans with a shared goal: to bring modern technology to an overlooked industry.
About the role 💼
You’ll own data science at Rundoo end-to-end: turning ambiguous business questions into crisp scopes, delivering robust analysis on predictable timelines, and building lightweight internal systems so insights are reproducible (not just a one-off notebook). You’ll be a thought partner to leaders across GTM, product, and finance — shaping the question as much as answering it — and proactively surfacing anomalies and opportunities as the business scales.
This is a remote role with a strong preference for candidates based in SF or NYC. You will report directly to the Head of Data Science.
What you’ll do as an Data Scientist at Rundoo 🗒️
Deliver high-trust analysis on clear timelines: stakeholders trust both the answer and the ETA; assumptions and limits are explicit.
Translate business problems into analysis + system requirements: turn vague asks into crisp scopes, metrics definitions, and data contracts.
Build and maintain internal decision systems: ship lightweight tools/workflows so insights are reproducible and maintainable by others.
Partner with GTM teams: help Sales/GTM move from “interesting analysis” to actions (e.g., prospecting lists, territory design, experimentation).
Proactively surface issues: detect anomalies, broken assumptions, or misallocated spend without waiting for a ticket.
Support fundraising readiness: contribute to an evergreen, credible data pool and reporting that leadership can rely on.
Requirements ☑️
5+ years of experience in data science, analytics, applied ML or MLE in a high-growth environment
Strong applied analytics / data science foundation (statistics, experimentation, causal thinking, forecasting, etc.).
Demonstrated ability to scope ambiguous problems and drive to decisions with stakeholders.
Comfort writing production-quality code (especially Python) and building maintainable internal systems (not just notebooks).
Excellent communication: can explain tradeoffs, assumptions, and recommendations to non-technical audiences.
High ownership and autonomy in a fast-paced environment; can operate without a lot of process.
Bonus points 🌟
Experience partnering closely with Sales/GTM teams (pipeline, conversion, pricing, prospecting, territories, etc.).
Experience building internal analytics tooling on cloud infrastructure (basic best practices, reliability, maintainability).
Experience operating in early-stage startups and/or building “v1 systems” that later scale.
Strong “structured systems thinking” and willingness to defend or revise an approach under scrutiny.
Location
Remote friendly
Expect ~1 week of travel per quarter to either our Chicago or Redwood City offices.
About the team 👥
You’ll partner closely with leaders across the business (GTM, product, and finance) and work directly with exec stakeholders. This is a high-trust, cross-functional role where the outputs need to be decision-ready and reproducible. You would work directly with the GTM leaders on the team:
Amrit (Data Science): Studied CS & English at Cornell; Data Scientist at Enigma; Public Interest Technology Fellow at the New York Public Library. Enjoys mending, maintenance & buying junk on eBay.
Matt (Sales): Studied history at Northwestern; taught middle school in Chicago (hardest job ever), led sales for a consumer start-up (Catch Co.), joined Rundoo as an AE and now leads the GTM team; former competitive angler in college (bass fishing 🎣)
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