What are some typical data scientist interview questions?

A data scientist is generally a though leadership level position. Assuming you’ve done your due diligence, you shouldn’t be wasting interview time with hypotheticals. Pick a data science problem that you’ve already solved, describe it in general terms, and ask the candidate how they would solve it. Have a discussion about the types of challenges you are facing and see what s/he has to say in response.

Remember when dealing with leadership level positions, the candidate is interviewing you just as much as you are interviewing them.

1. What are the differences between supervised and unsupervised learning?

2. How is logistic regression done

3. Explain the steps in making a decision tree.

4. How do you build a random forest model.

5. How can you avoid overfitting your model.

6. Differentiate between univariate, bivariate, and multivariate analysis.

7. What are the feature selection methods used to select the right variables.

8. In your choice of language, write a program that prints the numbers ranging from one to 50.

9. You are given a data set consisting of variables with more than 30 percent missing values. How will you deal with them?

10. What are dimensionality reduction and its benefits?

11. How should you maintain a deployed model?

12. What are recommender systems?

13. How do you find RMSE and MSE in a linear regression model?