Explain interest and influence stakeholders

You are interviewing for a Data Scientist role on a team that supports DoorDash's marketplace. Work through each prompt below in STAR form — Situation, Task, Action, Result — keeping every answer tight and concrete.

Ground your responses in how a three-sided marketplace actually behaves (consumers, dashers, merchants), and quantify outcomes wherever you can.

1. Why DoorDash now? Connect your answer to the company's mission, to the complexity of running a dense, multi-sided marketplace, and to how this particular role would stretch your own growth. Which recent change on the product or operations side interests you most, and what makes it compelling?

2. Project deep-dive: Walk through your highest-impact analytics project from beginning to end — the objective, the data you pulled, the modeling or experimentation approach, the calls you made from the results, and the measurable business gain. Which assumption felt least secure, and how did you go about testing it?

3. Influencing without authority: Describe an occasion when you used data to redirect a partner team's roadmap. How did you handle resistance from engineering or operations, and how did you get everyone aligned? Which specific metrics shifted?

4. Handling ambiguity and pace: Recall a situation where the problem was loosely defined and the timeline was aggressive. How did you create clarity and reduce execution risk? What trade-offs did you accept?

5. Ownership under failure: Talk about a launch of yours that degraded a guardrail metric — cancellations ticking up, for instance. How did you catch it, how did you communicate it, and how did you correct course? What did you change about your process afterward?

6. Career move: What is prompting you to leave your current role, and what distinctive value would you bring to this team in your first 90 days?

Constraints:

• Answer every prompt using the STAR structure.
• Keep each component to a few bullets; brevity matters.
• Back your claims with numbers and marketplace-level impact.
• Where relevant, explain how you would know your change worked.