How do Data Scientists handle imbalanced datasets?

Data scientists work with such imbalanced datasets by using techniques such as resampling, which may be in the form of oversampling the minority class or undersampling the majority class; other techniques that may be in place are synthetic data generation methods like SMOTE, meaning Synthetic Minority Over-sampling Technique, and using learning algorithms that are sensitive to the cost of misclassifying the minority classes.