KhataBook Data Scientist Interview Questions
The questions to prepare for a KhataBook Data Scientist interview. Questions from real interview reports rank first. Updated daily.
Determine the sample size needed to detect a meaningful A/B test effect at a chosen significance level and power.
Design a feature experiment with clear hypotheses, metrics, power, randomization, analysis rules, and safeguards against common pitfalls.
Determine sample size and power for a customer survey or experiment, including MDE, guardrails, and a disciplined decision rule.
Tests analytical judgment, adaptability, and ownership when evidence disproves an initial hypothesis.
Calculate each user's 7-day rolling order volume average, including calendar days with no orders.
Select, define, and validate a north star metric that represents sustained customer value and aligns teams with business outcomes.
Explain how to profile, clean, and standardize missing or dirty data before analysis.
Outline the first checks to diagnose a sudden drop in a core product metric, starting with data quality, scope, and decomposition.
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Calculate each user's seven-day rolling average of daily events using PostgreSQL window functions.
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