Beginner's Guide: Top 24 Job Interview Questions for Data Science

Data science interview questions can be tricky. During the data-scientist job interview, you may be asked questions about statistics, programming, data analysis, data pre-processing and modeling.

Consider focusing your job-interview prep on these top 24 common data science job interview questions:

1. What is logistic regression?
2. Why do we need evaluation metrics?
3. How is data science different from traditional application programming?
4. What is the difference between supervised and unsupervised learning?
5. What is a decision tree?
6. What is cross-validation?
7. What is a normal distribution?
8. What is a random forest algorithm?
9. What are univariate, bivariate and multivariate analyses?
10. How can we handle missing data?
11. What is the benefit of dimensionality reduction?
12. How can we deal with outliers?
13. What is ensemble learning?
14. What is the difference between machine learning and deep learning?
15. What is the difference between overfitting and underfitting?
16. What is regularization, and why is it useful?
17. What is selection bias?
18. What is the difference between a validation set and a test set?
19. What is the difference between regression and classification machine-learning techniques?
20. What are artificial neural networks?
21. What tools do you plan to use as a data scientist?
22. What is natural language processing, and how is it used?
23. What is normalization?
24. What is the difference between normalization and standardization?

This article was written by Davis David for HackerNoon and was lightly edited and republished with permission.