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.
You are designing an evaluation for a new rider-incentive program in a two‑sided ride‑hailing marketplace (riders request trips; drivers supply trips). The goal is to measure the program’s causal impact on demand, supply, and overall matching quality, while handling marketplace externalities.
Hints: Define treatment vs control; choose a unit of randomization; include engagement, earnings, conversion, wait time; consider externalities and heterogeneous effects.
Login required