Design analytics for a new-market launch
Company: DoorDash
Role: Data Scientist
Category: Analytics & Experimentation
Difficulty: hard
Interview Round: Onsite
DoorDash is entering a new city. Define the success metrics and guardrails for three phases: pre-launch (readiness), soft launch (limited zones/hours), and full ramp. For each phase: (a) list 3–5 core metrics with precise definitions (units, numerator/denominator, time window), (b) identify leading indicators vs outcome metrics, (c) propose guardrail thresholds that would trigger a rollback or hiring freeze. Then design a geo A/B or staggered rollout to estimate causal impact on orders and ETAs, addressing: seasonality, matched-control selection, spillovers across adjacent zones, novelty effects, and minimum-detectable-effect assumptions. Specify the decision rules you’d present to leadership to proceed/hold after two weeks.
Overview: This question evaluates a data scientist's competency in product analytics and causal inference, focusing on metric definition, guardrail setting, and experimental rollout design for a new-market launch.
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