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Evaluate Top-Dasher Program's Benefits and Challenges

Last updated: Mar 29, 2026

Quick Overview

This question evaluates proficiency in experimental design, causal inference, marketplace economics, metric-driven product analytics, and profitability modeling for a Data Scientist role within Analytics & Experimentation.

  • hard
  • DoorDash
  • Analytics & Experimentation
  • Data Scientist

Evaluate Top-Dasher Program's Benefits and Challenges

Company: DoorDash

Role: Data Scientist

Category: Analytics & Experimentation

Difficulty: hard

Interview Round: Onsite

##### Scenario DoorDash is considering several driver-facing initiatives: a Top-Dasher status, cash incentives, and a tiered rewards program. ##### Question For a potential Top-Dasher program, outline its key advantages and drawbacks and state whether you would launch it. If launched, what experiment or measurement framework would you use to quantify impact and define success? DoorDash wants to pay cash incentives to Dashers. How would you design a test to determine causal lift and decide whether the incentive is profitable? Propose a structure for a broader Dasher rewards program and explain how you would measure its effectiveness and iterate on it. ##### Hints Define treatment and control, choose primary and guardrail metrics (GMV, fulfillment rate, cost per order), compute incremental profit, check sample-size/power, consider driver selection bias, geographic stratification, seasonality, and long-term retention effects.

Quick Answer: This question evaluates proficiency in experimental design, causal inference, marketplace economics, metric-driven product analytics, and profitability modeling for a Data Scientist role within Analytics & Experimentation.

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DoorDash logo
DoorDash
Aug 4, 2025, 10:55 AM
Data Scientist
Onsite
Analytics & Experimentation
67
0

Scenario

DoorDash is considering several driver-facing initiatives: a Top-Dasher status, cash incentives, and a tiered rewards program.

Questions

  1. Top-Dasher program
  • Outline key advantages and drawbacks of a potential Top-Dasher status.
  • Make a go/no-go launch recommendation.
  • If launched, describe the experiment or measurement framework you would use to quantify impact and define success.
  1. Cash incentives
  • DoorDash wants to pay cash incentives to Dashers. How would you design a test to determine causal lift and decide whether the incentive is profitable?
  1. Broader Dasher rewards program
  • Propose a structure for a broader tiered rewards program and explain how you would measure its effectiveness and iterate.

Guidance to consider

  • Clearly define treatment and control; account for marketplace interference (supply-demand interactions).
  • Choose primary and guardrail metrics (e.g., GMV, fulfillment rate, cost per order, wait times, cancellations, Dasher retention).
  • Compute incremental profit, not just activity lift.
  • Check sample size/power; stratify by geography/time; handle seasonality.
  • Address selection bias, geographic stratification, and long-term retention effects.

Solution

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