Behavioral & Leadership (STAR) — Data Scientist, Marketplace

Context

You are interviewing onsite for a Data Scientist role focused on a multi‑sided marketplace (consumers, merchants, dashers). Answer concisely using STAR (Situation, Task, Action, Result). Be specific to DoorDash’s marketplace dynamics (supply–demand balance, ETAs, fulfillment, incentives, batching, ads, DashPass, DoubleDash, Drive/Storefront).

Questions

1. Why DoorDash now? Tie to the mission, marketplace complexity, and how this role advances your growth. Which recent product or ops change most excites you and why?
2. Project deep‑dive: Describe your most impactful analytics project end‑to‑end (goal, data, modeling/experiments, decisions, business lift). What was the shakiest assumption and how did you validate it?
3. Influencing without authority: Tell me about a time you changed a partner team’s roadmap using data. How did you handle pushback from engineering/ops and secure alignment? What concrete metrics moved?
4. Handling ambiguity and pace: Give an example where the problem was under‑specified and timelines were aggressive. How did you create clarity and de‑risk execution? What trade‑offs did you make?
5. Ownership under failure: Describe a time you shipped something that made a guardrail worse (e.g., cancellations ticked up). How did you detect it, communicate it, and correct course? What did you change in your process afterward?
6. Career move: Why are you leaving your current role, and what unique value will you bring to this team in your first 90 days?