DoorDash Director, Analytics, DashOS at DoorDash leads data science and analytics for DashOS platform supporting restaurant growth. Shapes measurement, guides strategy, and builds data foundations for decision-making.
Responsibilities
We’re looking for a Director of Data Science to lead a broad and high-impact portfolio supporting DashOS. In this role, you will shape how we measure success, guide product and commercial strategy, and build the data foundations that help teams move quickly and make better decisions across products at different stages of maturity. Success in this role means building a high-performing team, raising the quality and speed of decision-making, and helping DoorDash identify and scale the highest-ROI opportunities across the portfolio. You will report into a Senior Director on our Merchant Analytics team in our Analytics organization.
You’re excited about this opportunity because you will...
Lead and grow a team of data science and analytics leaders and practitioners across a portfolio that spans 0→1 products, products still being shaped and commercialized, and businesses already scaling quickly.
Own the analytical direction for the portfolio, including experimentation, KPI design, forecasting, decision support, funnel analytics, and foundational measurement.
Partner closely with Product, Engineering, Strategy & Operations, and Go-to-Market leaders to influence roadmap, commercialization, and investment decisions.
Build the operating system for decision-making by improving instrumentation, creating single sources of truth, and connecting short-term execution with long-term business outcomes.
Operate with broad scope and high autonomy in a startup-like environment while benefiting from the support and talent density of a scaled analytics organization.
We’re excited about you because...
You have 10+ years of experience in Data Science, Analytics, or a related quantitative field, including significant experience leading senior teams and developing managers.
You have strong product and business analytics judgment, with a track record of defining metrics, building decision frameworks, and influencing strategy in ambiguous environments.
You have deep expertise in experimentation and causal inference, and you are comfortable making decisions in settings with imperfect data, evolving products, and small or noisy samples.
You bring hands-on technical fluency in SQL and statistical analysis, and you can go deep enough to raise the technical bar for the team while operating effectively at a leadership level.
Qualification
10+ years of experience in Data ScienceHands-on technical fluency in SQL
Required
10+ years of experience in Data Science, Analytics, or a related quantitative field
Significant experience leading senior teams and developing managers
Strong product and business analytics judgment
Deep expertise in experimentation and causal inference
