Evaluate Rider-Incentive Program Impact with Key Metrics
Company: Uber
Role: Data Scientist
Category: Analytics & Experimentation
Difficulty: medium
Interview Round: Technical Screen
##### Scenario
The team plans to launch a new rider-incentive program and needs to evaluate its effectiveness across the marketplace.
##### Question
Propose an analysis/experiment to assess the impact of the rider-incentive feature.
List metrics for riders, drivers, and overall matching quality.
What additional metrics would you include and why?
Outline how you would measure these effects even if you know little about the feature’s internal design.
##### Hints
Define treatment vs. control, choose unit of randomization, include engagement, earnings, conversion, wait time, consider externalities and heterogeneous effects.
Quick Answer: This question evaluates a data scientist's skills in experimental design, causal inference, metrics engineering, and analysis for two‑sided marketplaces, with emphasis on measuring demand, supply, and matching-quality impacts while accounting for externalities and heterogeneous effects.