WTW Data Scientist Interview Questions
The questions to prepare for a WTW Data Scientist interview. Questions from real interview reports rank first. Updated daily.
Identify the main pitfalls that can distort A/B test interpretation and explain how to guard against them.
Evaluates power analysis and practical tradeoffs in experiment design.
Assesses understanding of false positives and how to control error rates in experiments.
Build a classifier for a highly imbalanced dataset and choose training and evaluation methods that surface rare positives.
Define a success metric for a new feature that captures real user value, not just raw usage.
Tests practical SQL window-function usage for cumulative and smoothed metrics.
Tests statistical reasoning for distinguishing signal from random variation.
Evaluates structured debugging of product metrics using data and experimentation thinking.
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