Manager, Data Science, Logistics Analytics

About The Team

Logistics Analytics helps Door Dash make better product, business, and go-to-market decisions through high-quality analytics, predictive modeling, experimentation, and strategic thought partnership. Our mandate for logistics is to fulfill our promise to Dashers, Consumers and Merchants by achieving seamless and reliable deliveries as efficiently as possible.

We’re hiring a Data Science Manager to lead analytics for the logistics pod and help shape high-priority product and business decisions. In this role, you will lead a team of data scientists, partner closely with Strategy & Operations, Product, Engineering, and business leaders, and turn ambiguous questions into clear recommendations that influence roadmap and plan outcomes. Success in this role means building a high-performing team, raising the quality and speed of decision-making, and ensuring analytics work is tightly connected to measurable business impact.

You will report into our Director, Data Science on the Dasher Logistics Analytics team in our Analytics organization.

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

• You have 6+ years of experience in analytics, data science, or a related quantitative field, including experience leading complex, ambiguous work from problem framing through recommendation.
• You have experience managing and developing data scientists or analysts and know how to set a high bar on quality, ownership, and impact.
• You have strong analytical fundamentals, including experimentation, predictive modeling, metric design, and translating data into actionable business decisions.
• You are an excellent cross‑functional partner and communicator who can influence stakeholders and tailor your message from working teams to senior leadership.
• You are highly effective at prioritization and know how to focus your team on the highest‑impact work in a fast‑moving environment.

The successful candidate’s starting pay will fall within the pay range listed below and is determined based on job‑related factors including, but not limited to, skills, experience, qualifications, work location, and market conditions. Base salary is localized according to an employee’s work location. Ranges are market‑dependent and may be modified in the future.

In addition to base salary, the compensation for this role includes opportunities for equity grants.

National base pay range for this position within the United States, including Illinois and Colorado: $184,300—$271,000 USD.

Door Dash offers a comprehensive benefits package to all regular employees, which includes a 401(k) plan with employer matching, 16 weeks of paid parental leave, wellness benefits, commuter benefits match, paid time off and paid sick leave in compliance with applicable laws (e.g. Colorado Healthy Families and Workplaces Act), medical, dental, and vision benefits, 11 paid holidays, disability and basic life insurance, family‑forming assistance, and a mental health program, among others.

• For salaried roles: flexible paid time off/vacation, plus 80 hours of paid sick time per year.
• For hourly roles: vacation accrued at about 1 hour for every 25.97 hours worked (e.g. about 6.7 hours/month if working 40 hours/week; about 3.4 hours/month if working 20 hours/week), and paid sick time accrued at 1…