Lead Data Scientist Interview Questions

409 lead data scientist interview questions shared by candidates

Code review: - Use of one-hot encoding over ordinal encoding - fixing the accuracy, precision, recall calculation, and explaining them - dropping the target before training the model - fitting the model on the train dataset instead of test - explaining the choice of model – random forest classifier, and the number of estimators i.e. trees (hyperparameter) - Why use validation dataset and then predict the test dataset? - Label mismatch in the train and test dataset (additional column in the train dataset) - Missing values in ‘age’ feature - How to handle missing values?
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Lead Data Scientist

Interviewed at Applied Data Science Partners

5
Jul 10, 2024

Code review: - Use of one-hot encoding over ordinal encoding - fixing the accuracy, precision, recall calculation, and explaining them - dropping the target before training the model - fitting the model on the train dataset instead of test - explaining the choice of model – random forest classifier, and the number of estimators i.e. trees (hyperparameter) - Why use validation dataset and then predict the test dataset? - Label mismatch in the train and test dataset (additional column in the train dataset) - Missing values in ‘age’ feature - How to handle missing values?

One or 2 questions on CV, or why McKinsey. Which model design works best given the data, and why, which Metric works best etc. Consulting Math with pen and paper only. Ability to compute probabilities, regression results etc. without calculator. Ability to explain what certain ML results on a screen actually meant.
avatar

Lead Data Scientist

Interviewed at McKinsey & Company

4.1
Jan 6, 2022

One or 2 questions on CV, or why McKinsey. Which model design works best given the data, and why, which Metric works best etc. Consulting Math with pen and paper only. Ability to compute probabilities, regression results etc. without calculator. Ability to explain what certain ML results on a screen actually meant.

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