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Gopuff
E-commerce & Online Marketplaces
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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.
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.
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.
Forecast demand: Build accurate, well-calibrated demand forecasts at the right granularity (location × time) to inform driver supply planning, scheduling, incentives and pricing decisions.
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.
Own solutions end to end: frame the problem, build features and models, deploy with engineering partners, then monitor, explain and improve performance in production.
Partner with product, engineering, operations and finance to turn ambiguous business questions into well-defined technical objectives and shipped solutions.
Deeply understand our customers, delivery partners and data to find new opportunities for ML, optimization and causal inference.
MS or PhD in Operations Research, Mathematics, Statistics, Economics, Computer Science, Engineering or a related field, with 2+ years of experience in delivery, logistics, marketplace or pricing problems (or 8+ years of industry experience in data science).
Strong background in at least two of the following: pricing/revenue optimization, mathematical optimization (e.g., MIP, assignment and routing problems, heuristics), time-series and demand forecasting, experimentation and causal inference.
Hands-on experience designing experiments in two-sided or operational marketplaces where standard A/B tests break down (e.g., switchback or cluster-randomized designs, variance reduction).
A proven ability to translate ambiguous business problems into clear technical objectives and deliver concrete, measurable results.
Expertise in machine learning and statistics.
Proficiency in Python, SQL and source control; experience shipping models to production with engineering teams.
Experience in on-demand delivery, ride-hailing or gig-economy marketplaces.
Familiarity with optimization solvers (e.g., OR-Tools, Gurobi) and forecasting libraries.
Experience with ETA prediction or driver incentive and pay design.
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