G

Gopuff

Direct-to-consumer delivery of convenience items

Senior Data Scientist - Delivery Tech

Data ScienceConfirmed live in the last 24 hours
Full-timeRemote in USARemote

About the Job

Requirements

  • A Master of Science or PhD in Operations Research, Mathematics, Statistics, Economics, Computer Science, Engineering, or a related field, with 2 or more years of experience in delivery, logistics, marketplace, or pricing problems, or 8 or more years of industry experience in data science.
  • A strong background in at least two of pricing or revenue optimization, mathematical optimization such as mixed-integer programming, assignment and routing problems or heuristics, time-series and demand forecasting, and experimentation and causal inference.
  • Hands-on experience designing experiments in two-sided or operational marketplaces where standard A/B tests break down, such as switchback or cluster-randomized designs and variance reduction.
  • Expertise in machine learning and statistics.
  • Proficiency in Python, SQL, and source control, and experience shipping models to production with engineering teams.

Responsibilities

  • Design, build, and iterate on algorithmic delivery fee strategies, such as dynamic or contextual pricing by location, time, basket, and capacity, balancing conversion, customer experience, and profitability.
  • Develop optimization and machine-learning approaches to order batching, assignment, and routing to lower overall delivery cost while maintaining speed and reliability.
  • Build accurate, well-calibrated demand forecasts at the appropriate location-and-time granularity to inform driver supply planning, scheduling, incentives, and pricing decisions.
  • Design and analyze high-quality experiments, including A/B, switchback, and geo- or market-level designs that account for marketplace interference, and use causal inference to measure impact on customer and business metrics.
  • Own solutions end to end: frame the problem, build features and models, deploy with engineering partners, and 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.
  • Understand customers, delivery partners, and data to identify opportunities for machine learning, optimization, and causal inference.

Desired Qualifications

  • Experience in on-demand delivery, ride-hailing, or gig-economy marketplaces.
  • Familiarity with optimization solvers such as OR-Tools or Gurobi, and forecasting libraries.
  • Experience with ETA prediction or driver incentive and pay design.

About the Company

Gopuff

Direct-to-consumer delivery of convenience items

GoPuff is a digital delivery service that brings a wide range of everyday items directly to customers’ doors, including convenience items, snacks, beverages, and even alcohol. Customers place orders through the GoPuff app or website, and GoPuff handles inventory and delivery through its own network, charging for the items plus a delivery fee. Revenue comes from product sales and delivery charges, with occasional discounts and promotions to attract shoppers. Unlike many rivals, GoPuff emphasizes rapid, door-to-door delivery across a broad product lineup, relying on its own stock and logistics to speed up service. The company aims to make it fast and easy for people to get daily essentials without leaving home.

Company size
1,001-5,000
Company stage
Late Stage VC
Total funding
$5.2B
Headquarters
Philadelphia, PA
Founded
2013

Recently Posted Jobs

Explore more opportunities at Gopuff

See more jobs