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.
MediumTechnical
0 practiced
Design a merchant-facing dashboard to help restaurants monitor fulfillment performance and profitability on DoorDash. Specify core KPIs, key visuals (with reasoning), necessary transformations (e.g., cost-per-order), refresh cadence, and how you would support merchant interpretation through tooltips or notes.
MediumSystem Design
0 practiced
Pick a DoorDash feature (for example, subscription product DashPass, scheduled delivery, or pickup). Outline an end-to-end BI dashboard design to monitor adoption and business impact. Include: primary metrics, segmentation, required data sources, refresh cadence, and at least two alerts you would configure.
MediumTechnical
0 practiced
DoorDash runs thousands of experiments. Describe how you would build an internal experimental results dashboard that allows PMs to check experiment health (sample size, duration, lift, p-values), flags potential issues (peeking, unbalanced segments), and surfaces actionable recommendations. Include data inputs, key UI elements, and guardrails.
EasyTechnical
0 practiced
DoorDash encourages experimentation and rapid product iteration. Provide a concrete example from your experience where A/B test results led you to recommend a change. Include: hypothesis, primary metric(s), sample size considerations, statistical significance or confidence intervals, and the final business action.
EasyTechnical
0 practiced
Explain how DoorDash's two-sided marketplace business model creates opportunities for a BI Analyst to drive value. List three analytics use-cases, each tied to a stakeholder (consumer, merchant, or dasher), describe the expected business outcome, and mention what data sources you would use for each use-case.
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