Evaluate Marketplace Changes
Company: Uber
Role: Data Scientist
Category: Analytics & Experimentation
Difficulty: medium
Interview Round: Onsite
Overview: This question evaluates a data scientist's competency in experimental design, causal inference, metrics instrumentation, A/B testing, and marketplace analytics within the Analytics & Experimentation domain, focusing on both conceptual understanding of bias, interference, and decision framing and practical application of randomization, metric selection, and heterogeneity analysis. It is commonly asked to assess the ability to define clear decision goals, identify primary and guardrail metrics, determine the correct unit of randomization or analysis, understand when experiments versus quasi-experimental designs are appropriate, and anticipate sources of bias or interference across regions, drivers, merchants, and users.
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