Your question is Feature Engineering for Recs. Take a moment with it on the right.
Talk me through your thinking if you like. When you're confident, submit your answer and I'll grade it like a real screen (7/10 or better passes).
What techniques do you use for feature engineering in recommendation systems?
Discuss how you would construct user, item, interaction, and contextual features for ranking recommendations. Explain how you would prevent temporal and behavioral leakage, represent cold-start entities, handle sparse categorical data, and validate whether engineered features improve ranking quality. Include a practical implementation approach and the metrics you would use.
