Investigate Causes of Cold Food Deliveries and Solutions
Company: DoorDash
Role: Data Scientist
Category: Analytics & Experimentation
Difficulty: medium
Interview Round: Technical Screen
##### Scenario
Customers complain that delivered food often arrives cold. As the data scientist for the delivery quality (Dasher) team, you must diagnose the problem and design a solution.
##### Question
How would you investigate the root causes of cold food deliveries? Which metrics would you track, and what data would you pull? Design an experiment to test a mitigation (e.g., insulated bags, optimized routing). Detail hypothesis, treatment, control, unit of randomization, success metrics, and runtime calculation.
##### Hints
Frame with funnel analysis (prep, pickup, travel time), define quantitative temperature proxy, consider staged A/B test across zones, monitor delivery time, reorder-rate, and complaint-rate.
Quick Answer: This question evaluates a data scientist's competency in diagnostic analytics, causal inference, experiment design, metric definition, funnel analysis, and sample size estimation.