Measure causal impact of YouTube ads

Company: Google

Role: Data Scientist

Category: Analytics & Experimentation

Difficulty: medium

Interview Round: Onsite

Quick Answer: This question evaluates causal inference and experimental design skills for marketing measurement, including competency in identifying confounders, designing geo-level randomized or quasi-experimental comparisons, modeling ad-stock/lagged effects, conducting power/sample-size calculations, detecting spillovers, and aggregating heterogeneous treatment effects. It is commonly asked to test practical ability to justify identification assumptions and diagnostics in Analytics & Experimentation, assessing both conceptual understanding of causal frameworks and hands-on practical application of experimental and time-series methods.