Senior Data Scientist

Remote from: USA
Salary, yearly, USD: 201,000 - 248,000
Department: Data Science & Analytics
Employment type: Full Time,
Job posted: 9 Jun 2026
Apply before: 9 Jul 2026
Experience level: Senior
Views / Applies: 34 / 9

Powering the future of paint and hardware stores with modern technology.

Computer Software
2021

AI Summary

Rundoo is seeking a Senior Data Scientist to own data science end-to-end, from scoping ambiguous business questions to building reproducible internal systems. The role involves partnering with GTM, product, and finance leaders to drive data-informed decisions. Candidates need 5+ years of experience in high-growth environments, strong analytics and coding skills, and high autonomy. The company offers a competitive salary and the flexibility of remote work with occasional travel.

Role DNA

Job Complexity

Easy Hard

Pace & Pressure

Relaxed Fast-paced

Autonomy Level

Guided Full Ownership

Communication Load

Independent Highly Collaborative

AI Insight This role demands a senior data scientist with 5+ years experience, strong analytical and coding skills, and ability to operate autonomously in a fast-paced environment, tackling ambiguous problems. Hence difficulty is rated 4.

Salary Analysis

AI Insight The offered salary range of $201,000-$248,000 is above the typical market range for senior data scientists in the US, which spans $130,000-$200,000. This indicates a highly competitive compensation package, reflecting the seniority and high expectations of the role.

Key Skills

Data Science Python Statistics Experimentation Causal Inference Machine Learning Analytics Cross-functional Collaboration GTM Strategy SQL

Cover Letter Sample

Dear Hiring Manager,

I am thrilled to apply for the Senior Data Scientist position at Rundoo. With over five years of experience in data science and analytics within high-growth startups, I have a proven ability to transform ambiguous business questions into clear, actionable insights. I am particularly inspired by Rundoo's mission to modernize independent supply stores and am confident that my technical skills in Python, statistics, and experimentation, combined with my experience partnering with GTM and product teams, would allow me to drive significant impact. I look forward to the opportunity to build robust data systems and contribute to Rundoo's continued success.

Sincerely,

[Your Name]

Possible Interview Questions

Describe a time you turned an ambiguous business question into a clear data science project. What was your approach?

In my previous role, a product manager asked 'Why are our activation numbers dropping?' I first clarified the goal by asking about the business impact. I then defined activation as a composite metric, explored cohort trends, and discovered a correlation with a recent UI change. I designed an experiment to test the new UI, resulting in a recommendation to revert the change, which improved activation by 10%.

How do you ensure your analysis is reproducible and maintainable by others?

I follow software engineering best practices: using version control, writing modular Python code with clear documentation, and building automated pipelines. For one-off analyses, I convert them into reusable scripts or dashboards. I also maintain a data dictionary and ensure assumptions are explicitly stated.

Can you explain a time you influenced a business decision using data, despite the data being incomplete or noisy?

During a product launch, our sales data had limited post-launch info. I used a Bayesian approach to model conversion rates with prior information from similar launches. I presented the results with credible intervals, highlighting the uncertainty. The VP of Sales used this to adjust the sales forecast and set realistic targets.

Describe your experience with causal inference. How have you applied it in a business context?

I used difference-in-differences to evaluate a pricing change's impact on customer retention. By comparing the treated group to a control group over time, I isolated the effect of the price change from seasonal trends. The analysis showed a 5% increase in retention, leading to a permanent roll-out.

How do you prioritize your work when multiple stakeholders have competing requests?

I start by understanding each request's business impact and urgency. I often create a simple framework (e.g., impact vs. effort) to align stakeholders. For example, when both marketing and product needed analysis, I proposed a quick win for marketing while developing a more comprehensive model for product. Regular check-ins ensure transparency.

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 🎣)
Vidhan (Client Experience): Studied Biomedical Engineering and Econ at Duke University; Formerly Director of Product at BuildZoom, Product lead at Hinge Health, and Co-Founder of Urova Medical.

Interview Process 🎤

Intro call (30 min)
Take-home exercise overview (30 min)
Paid Take Home (~4-6 hours) — This is the core of the interview. We’ll share more information about Rundoo and ask you to complete a task representative of the work you’d do at Rundoo. This interview will be paid, and we ask that you dedicate significant time to it.
On-site
- Take-home review – pressure-test the analysis; reproduce numbers; push on assumptions
- GTM collaboration – test trust/translation and move from analysis to action.
- Lunch with the team
- Problem solving discussion – informal discussion on how problems are approached and tools used.
- Systems/engineering – Basic systems architecture and best practices for building an internal tool.
- Culture – Behavioral questions, geared toward our culture & values.
References: one manager, one peer, one stakeholder (PM/GTM/Finance).

Benefits 🏋️

Full medical, dental, and vision coverage (100% of premiums for you, 50% for dependents)
401k with Betterment
Unlimited PTO with 10 company paid holidays
Gym allowance
Daily team lunches for those in office
Learning materials and audiobook subscriptions
Dog-friendly office in Redwood City – https://rundoo.ai/rundogs/

About our founders 🌲

Andrew (CTO): studied computer science & humanities at Stanford; worked as a software engineer and head of engineering at Apple & Anova; danced with the SF ballet (where he met his wife)! 🩰
Nick (CEO): studied math & computer science at Stanford; worked as a trader at Bridgewater & Citadel and as a PM at Google & Enigma; distantly related to the founder of the Hershey company 🍫

How we’ve fundraised 💰

We’ve raised $18m across three rounds:

A $2m pre-seed led by Kent Bennett at Bessemer with participation from Plug & Play, Quiet Capital, and Sequoia.
A $5m seed led by Caitlin Bolnick Rellas at CRV.
An $11m series A led again by Bessemer and CRV.

Apply now >