If you’re preparing for DoorDash Analytics & Experimentation interview questions, expect rounds that probe both statistical rigor and marketplace intuition. DoorDash’s analytics roles often focus on A/B testing design and analysis, metric definition and guardrails, SQL fluency for slicing large production tables, and the ability to diagnose changes in key metrics across time and cohorts. Interviews typically evaluate your experiment-design tradeoffs (unit of randomization, power, novelty and network effects), your storytelling with numbers, and your capacity to translate findings into operational decisions that balance customer, merchant, and Dasher outcomes. For interview preparation, practice live SQL problems, end-to-end experiment design cases, and concise behavioral stories that highlight impact and stakeholder communication. Emphasize thinking through marketplace-specific pitfalls such as supply-demand interactions, heterogeneous treatment effects, and production monitoring; show you can propose sensible tradeoffs and guardrail metrics. Mock interviews with real experiment scenarios, timed SQL drills, and clear, metric-driven narratives will make your answers sharper and more directly relevant to what DoorDash hires for in analytics and experimentation.