Motivation for DoorDash and Data Science Role Questions
Topic covers motivation for applying to DoorDash and specifically to a Data Science role, including alignment with DoorDash's mission, product strategy, and data-driven decision making, as well as demonstrating cultural fit and value you bring to the team.
EasyTechnical
0 practiced
Describe a small project (2–4 weeks) you would propose to demonstrate value as a new ML Engineer at DoorDash. State the hypothesis, data required, modeling approach, expected metric improvements, and how you would ship it quickly.
EasyBehavioral
0 practiced
What motivates you specifically about building ML systems for merchants (e.g., demand forecasting, menu personalization) at DoorDash? Provide one practical example of a model or feature you'd be excited to develop for merchants and why it matters.
MediumTechnical
0 practiced
Reflecting on DoorDash’s mission to empower local economies, propose an ML-driven initiative that favors local merchant discovery and benefits small businesses. Describe the modeling approach, business metrics, and how you would avoid unintended harms like over-promotion of certain merchants.
MediumBehavioral
0 practiced
DoorDash prides itself on fast iteration. Describe a time you took an ML prototype from concept to production under tight deadlines. Which decisions did you make for speed, what did you postpone, and how does that approach align with DoorDash’s product cadence?
HardTechnical
0 practiced
As an ML Engineer at DoorDash, how would you build trust with merchants when deploying recommendation/personalization models that affect their orders and revenue? Include technical, measurement, and communication steps.
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