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This is a hard difficulty Analytics & Experimentation question, commonly asked during HR Screen rounds at Meta.

What role is this question designed for?

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

Design a clustered A/B test with spillovers

Last updated: Mar 29, 2026

Quick Overview

This question evaluates a data scientist's understanding of cluster-randomized experiments with spillovers, covering causal inference under interference, intracluster correlation and power/sample-size calculations, cluster formation and balance checks, staggered-adoption analysis, and metrics and multiple-testing control.

hard
Meta
Analytics & Experimentation
Data Scientist

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Design a clustered A/B test with spillovers

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