Deskripsi Pekerjaan
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to lumber to flooring, over 200,000 such stores across the country sell over $1T of building materials annually using outdated, on-premises systems.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, reliab