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This is a medium difficulty Statistics & Math question, commonly asked during Technical Screen rounds at Google.

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

Determine Impact of New Chat-Notification on User Engagement

Last updated: Mar 29, 2026

Quick Overview

This question evaluates a candidate's competency in causal inference, experimental design, and statistical validation for measuring the effect of a notification feature in a messaging product.

Google

Aug 4, 2025, 10:55 AM

Data Scientist

Technical Screen

Statistics & Math

Scenario

A product team wants to determine whether a new chat-notification design increases daily active users (DAU) in Google Workspace Chat.

Task

Design a causal inference study to estimate the notification feature’s impact on engagement. Include:

Identification strategy (primary and backup).
Required data (unit of analysis, metrics, covariates).
Key assumptions for identification.
How you would validate/diagnose those assumptions and ensure robustness.

Assume the feature can be rolled out via a server-side flag, with the possibility of randomized rollout or observational/staggered adoption.

Solution

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