Explain why DoorDash and job change
Overview
This question evaluates a data scientist's cross-functional leadership, marketplace and operations judgment, and ability to quantify trade-offs across customer experience, worker earnings, cost, and reliability within a behavioral & leadership interview for a Data Scientist role.
DoorDash
Oct 13, 2025, 9:49 PM
Data Scientist
Onsite
Behavioral & Leadership
0
0
Behavioral & Leadership (Onsite) — Data Scientist
Context
You are interviewing for a Data Scientist role focused on marketplace and operations. Use concrete, recent (≤12 months) examples, quantify impact, and explain the trade-offs you made across customer experience, dasher experience/earnings, cost, and reliability.
Questions
- Why DoorDash, and why now?
- Cross-functional decision under time pressure
- Give one specific example from the last 12 months where you proactively drove a decision with product, operations, and engineering under time pressure.
- Quantify your impact (e.g., conversion, cancellations, delivery time, cost, dasher earnings/EPH, acceptance rate).
- Explain the exact metric trade-offs you accepted and why.
- Career move
- Why are you leaving your current role? What concrete limitations are you looking to overcome here?
- Marketplace trade-off: customer wait time vs. dasher earnings
- Describe a time you navigated tension between improving customer wait time and maintaining dasher earnings.
- What was your decision rubric? How did you handle stakeholder pushback in the moment? If you had to redo it, what would you change?
Note: Use a structured approach (e.g., STAR: Situation, Task, Action, Result). Keep answers specific and quantitative.
Solution
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