Diagnose Strong Validation and Weak Production Performance
Company: Bridgewater
Role: Machine Learning Engineer
Category: Machine Learning
Difficulty: medium
Interview Round: Technical Screen
Overview: Diagnose why a model shows strong validation metrics but performs poorly in production by ranking and testing competing hypotheses. Examine leakage, split design, training-serving preprocessing parity, normalization, drift, cohort metrics, label quality, and a safely versioned rollout.