Your question is Handling Imbalanced Data in Production. 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).
How would you handle imbalanced datasets in a production environment?
Explain how you would diagnose the imbalance, choose between class weighting and resampling, select appropriate evaluation metrics and decision thresholds, and prevent leakage during validation. Address deployment concerns such as calibration, changing class prevalence, monitoring, retraining, and the operational cost of false positives versus false negatives. Provide a concise implementation outline using a representative tabular binary-classification dataset.