Manager, Data Science

DoorDash DoorDash · Consumer · San Francisco, CA · 331 Analytics

Manager, Data Science for Merchant Analytics team at DoorDash. This role involves leading a team of data scientists to provide analytics, predictive modeling, and decision support for product, business, and go-to-market priorities. The manager will partner with cross-functional leaders, define success metrics, build measurement frameworks, and use experimentation to drive business outcomes. Success requires building a high-performing team, ensuring analytical rigor, and scaling analytics frameworks.

What you'd actually do

  1. Lead and develop a team of data scientists responsible for high-impact analytics, predictive modeling, and decision support tied to DoorDash’s most important product, business, and GTM priorities.
  2. Partner closely with Strategy & Operations, Product, Engineering, and business leaders to shape decisions, influence roadmaps, and improve plan-critical metrics.
  3. Define success metrics, build measurement frameworks and predictive models, and use experimentation and analysis to connect product and operational levers to business outcomes.
  4. Build a high-performing pod that balances analytical rigor, strong prioritization, and clear storytelling in a fast-moving environment.
  5. Scale reusable analytics frameworks, tools, models, and best practices that make the broader organization more effective over time.

Skills

Required

  • 6+ years of experience in analytics, data science, or a related quantitative field
  • experience leading complex, ambiguous work from problem framing through recommendation
  • experience managing and developing data scientists or analysts
  • strong analytical fundamentals, including experimentation, predictive modeling, metric design, and translating data into actionable business decisions
  • excellent cross-functional partner and communicator
  • highly effective at prioritization

What the JD emphasized

  • leading complex, ambiguous work from problem framing through recommendation
  • managing and developing data scientists or analysts
  • analytical rigor
  • strong prioritization
  • clear storytelling