Build a Churn Prediction Model
Company: Gusto
Role: Data Scientist
Category: Machine Learning
Difficulty: medium
Interview Round: Onsite
Overview: This question evaluates a candidate's competency in end-to-end churn modeling, including precise label definition, point-in-time feature engineering and leakage prevention, handling imbalanced/rare positive classes, ranking-focused evaluation, model selection, production scoring cadence, and explainability for stakeholders.