Senior Data Scientist
Rundoo
| Company | Rundoo |
| Category | Data & Analytics |
| Location | Remote |
| Remote | Remote |
| Employment | Not stated |
| Level | Senior |
| Salary | USD 201k–248k |
| Posted | 9 Jun 2026 |
| Last verified | 30 Jul 2026 |
| Source | Employer career page (ashby) |
Description
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to lumber to flooring, over 200,000 such stores across the country sell over $1T of building materials annually using outdated, on-premises systems.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:
1. Amrit https://www.linkedin.com/in/amrit-kwatra-87066612a/ (Data Science): Studied CS & English at Cornell; Data Scientist at Enigma; Public Interest Technology Fellow at the New York Public Library. Enjoys mend
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