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This is a medium difficulty Machine Learning question, commonly asked during Technical Screen rounds at Uber.

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This question is commonly asked for Data Scientist candidates at Uber during technical interviews.

Evaluate Promotions for Uber Eats Users | Uber Interview Question

Evaluate Promotions for Uber Eats Users

Last updated: May 2, 2026

Quick Overview

This question evaluates competency in experimental design, causal inference, A/B testing, metric selection, and quantifying promotion impact for a food-delivery platform, including identification of confounders, heterogeneous treatment effects, cost considerations, cannibalization, and marketplace interference.

Uber

Apr 30, 2026, 12:00 AM

Data Scientist

Technical Screen

Machine Learning

Uber Eats wants to send promotions or coupons to users. Design an experiment and analysis plan to evaluate whether the promotion is effective.

Address the following:

What are the primary business metrics and guardrail metrics?
What should be the randomization unit?
How would you define treatment and control groups?
What confounding factors could bias the analysis?
How would you avoid or adjust for those confounders?
How would you handle promotion cost, cannibalization, heterogeneous treatment effects, and marketplace interference?
How would you decide whether to launch the promotion?

Solution

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