Design experiment for homepage tab replacement
Company: Roblox
Role: Data Scientist
Category: Analytics & Experimentation
Difficulty: hard
Interview Round: Technical Screen
Roblox plans to replace an existing homepage tab with a new tab. Design a rigorous experiment to evaluate the causal impact of this replacement at the user and ecosystem levels. Assume today is 2025-09-01. Specify: (1) the experimental unit (e.g., user-level vs. device-level) and randomization scheme that avoids cross-device contamination; (2) primary success metrics (e.g., D1/D7 retention, homepage click-through, session length, conversion to play, creator impressions/engagement, revenue) and guardrails (crash rate, latency, abuse, fairness of content distribution); (3) how you will mitigate and measure novelty and navigation-friction effects when a tab is removed (e.g., ramp plan, cooldowns, or holdout re-exposure); (4) how to handle ecosystem interference/network effects (e.g., switchback or geo experiments, creator-level holdouts); (5) the metric definitions at a user-day grain and whether to use CUPED or pre-exposure covariates; (6) sample size/power calculations for a 1% relative lift in D7 retention with 80% power and α=0.05, including assumptions and minimum test duration under weekly seasonality; (7) decision thresholds and rollback criteria; (8) what diagnostics you would run if click-through rises but D7 retention falls; (9) a follow-up analysis plan if the treatment cannibalizes time from other tabs but increases long-term retention (e.g., 2x2 or crossover design, or diff-in-diff with staggered rollout).
Quick Answer: This question evaluates experiment design and causal-inference competency for product changes that impact both end users and platform creators, covering randomization strategies, metric and guardrail selection, power calculations, and handling of novelty, navigation friction, and ecosystem interference.