Data Scientist
US$160,000 – US$200,000 / yr base salary
Posted 14 Oct 2026
Advertised as “Senior Data Scientist - Delivery Tech”
BranchFactor Summary
The original posting with the fluff stripped out
- Expected experience
- 2+ yrs
- Management level
- Individual contributor
- Employment
- Remote
- Contract
- Full-time
| Base salary | US$160,000 – US$200,000 / yr |
|---|
Field of studyComputer Science, Economics, Engineering, Mathematics, Operations Research, Statistics (or related)
Study levelMaster's or higher
Are you passionate about data science? Do you describe yourself as an innovative problem solver? Looking for an opportunity that will directly impact the customer experience at Gopuff? Come join the Gopuff Data Science team and #ChangeTheGame. Gopuff is a high-growth startup that is revolutionizing hyper-local instant e-commerce. We warehouse and deliver tens of thousands of products to your door super fast.
As a Senior Data Scientist at Gopuff working on the Delivery Technology Team, you will lead the vision and delivery of data driven models to optimize the delivery experience for consumers and delivery partners on our platform across dispatch optimization, delivery routing/ETAs, driver pricing/incentives, as well as the delivery partner experience. All of that, with a direct impact on the delivery experience that is so core to serving our customers’ immediate needs, means you’ll have the opportunity to make a huge impact on the future success of Gopuff.
We’re looking for a doer, problem solver, and thought-leader.
What We Offer
- Medical/Dental/Vision Insurance
- 401(k) Retirement Savings Plan
- HSA or FSA eligibility
- Long and Short-Term Disability Insurance
- Fitness Reimbursement Program
- 25% employee discount & FAM Membership
- Flexible PTO
- Group Life Insurance
- EAP through AllOne Health (formerly Carebridge)
You Will
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Optimize delivery fees: Design, build and iterate on algorithmic delivery fee strategies (e.g., dynamic or contextual pricing by location, time, basket and capacity) that balance conversion, customer experience and profitability.
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Solve the driver dispatch problem: Develop optimization and ML approaches to order batching, assignment and routing that lower overall delivery cost while keeping speed and reliability high.
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Forecast demand: Build accurate, well-calibrated demand forecasts at the right granularity (location × time) to inform driver supply planning, scheduling, incentives and pricing decisions.
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Run rigorous experiments: Design and analyze high-quality tests, including A/B, switchback and geo/market-level designs, that account for marketplace interference, and use causal inference to measure true impact on customer and business metrics.
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Own solutions end to end: frame the problem, build features and models, deploy with engineering partners, then monitor, explain and improve performance in production.