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DoorDash Business Model & Trade-offs Questions

Analysis of DoorDash's business model within a platform-based marketplace context, including revenue streams (delivery fees, commissions, subscription), cost structure (logistics, driver incentives), partnerships, pricing strategies, market expansion decisions, and the strategic trade-offs between growth, profitability, and delivering value to customers.

EasyTechnical
43 practiced
Design an A/B test to evaluate reducing the delivery fee by $0.50 for new customers. Specify experiment population and eligibility criteria, randomization scheme and stratification variables, the primary and secondary metrics, minimum detectable effect with sample size assumptions, required experiment length, and potential risks such as interference, fraud, or business leakage.
HardTechnical
51 practiced
A proposed personalization feature would set higher delivery fees in wealthier neighborhoods to boost driver earnings and platform revenue. Discuss the ethical, legal, and business trade-offs of such a policy. As a Data Scientist, outline the analyses you would run to quantify disparate impact, alternative designs that achieve earnings objectives with less biased outcomes, and how you would present recommendations to leadership.
HardTechnical
43 practiced
You have a fixed monthly subsidy budget to increase GMV in underperforming neighborhoods. Formulate an optimization problem to allocate subsidies across neighborhoods to maximize expected incremental GMV subject to the budget and fairness constraints. Define the objective, constraints, how to estimate neighborhood-level uplift curves, and describe an algorithmic approach to solve this under uncertainty at scale.
HardTechnical
54 practiced
Propose a system to detect and mitigate fraudulent orders or collusion patterns on DoorDash (for example fake orders to claim promotions). Describe candidate feature sets, supervised and unsupervised detection approaches, real-time scoring constraints, feedback loops with investigations and human review, thresholds for blocking vs manual review, and evaluation metrics emphasizing precision and recall trade-offs.
HardTechnical
49 practiced
Case: A national restaurant chain proposes an exclusivity deal with DoorDash in select markets that lowers commission but promises large order volume uplift. As a Data Scientist, propose an analysis plan to evaluate this deal: model expected incremental GMV, merchant economics for both parties, cannibalization of other channels, long-term retention effects, sensitivity analysis, and negotiation levers such as duration and performance-based tiers.

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