University of British Columbia Data Scientist Interview Questions
The questions to prepare for a University of British Columbia Data Scientist interview. Questions from real interview reports rank first. Updated daily.
Explain an A/B test end to end, including hypothesis, metrics, power, randomization, analysis, pitfalls, and the launch decision.
Identify major online experimentation pitfalls and explain practical mitigations for SRM, network effects, peeking, and novelty.
Design an A/B test for a new platform feature, including success metrics, power, guardrails, and a clear ship decision.
Tests mentorship, collaborative leadership, knowledge sharing, and ownership of team development.
Tests adaptability, research judgment, prioritization, and ownership when unexpected constraints disrupt a study.
Explain how window functions differ from GROUP BY and when to use each in Splice product analysis.
Build a systematic process to validate, decompose, and explain a sudden 10% drop in core engagement.
Explain what statistical significance means and why it matters when interpreting experimental or analytical results.
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Write a SQL query to identify the top 10% of creators based on engagement metrics over the last 30 days. Use the provided creators and creatorengagements ...
TikTokCount valid daily interactions and return the top three users using aggregation and deterministic ranking.
Calculate each user's 7-day rolling transaction average and daily spend rank using PostgreSQL window functions.
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