Design a baseline loan recommendation system
ShopifyMachine Learning Engineer · Onsite
Last updated
This question evaluates understanding of ML-driven recommendation and credit-risk systems, including skills in personalization, feature design, risk calibration, fairness and regulatory compliance, explainability, and operational monitoring.
Design a baseline system to recommend loans to users. Define the objective(s) and constraints (e.g., approval likelihood, default risk, user experience, regulatory and fair lending requirements); describe features for users and loan products, handling cold-start and missing data; choose a simple yet defensible modeling approach (e.g., logistic ranking with calibrated risk), outline offline metrics and online experiment design, discuss bias/feedback-loop mitigation, safety checks, and a phased rollout and monitoring plan.
Solution walkthrough is for members
Get the full walkthrough with reference code and complexity analysis, plus Kitty Coach at 300 messages a day. Hints, the code runner and community answers stay free.