Data Scientist Interview Questions

The demand for Data Scientists has seen a significant growth in recent years thanks to the increasing size of data.

A Data Scientist is a very technical role and requires a varied and unique set of skills. Therefore, an interview will certainly explore both your technical skillset and also test you on your practical knowledge too. This role also includes a lot of communication regarding the data analysis findings and what decisions should be made from them.

It’s important to ensure that when you are invited to interview for a

The key technical skills for a Data Scientist revolve round statistics and machine learning.

1. What is Singular Value Decomposition?
2. Why is a comma considered a bad record separator or delimiter?
3. What is the difference between interpreted computer language and compiled computer language?
4. How do you handle missing data? What imputation techniques do you recommend?
5. What’s more important: predictive power or the interpretability of a model?
6. Can you give an example of a data cleaning technique that you have used in the past?
7. Describe a situation where you had to make a decision between two different types of analysis and why you chose the one you did?
8. Could you compare the differences between SAS, Python, R and Perl?
9. What is A/B testing and how is it different from usual hypothesis testing?
10. What is NLP and how is it related to Machine Learning?
11. Do you know what Type-I/Type-II errors are?
12. What is the difference between data for usual statistical analysis and time series data?
13. How do you identify and overcome obstacles regarding projects, customers and decision makers?
14. Tell me the difference between a convex function and non-convex?

By preparing answers to the most common Data Scientist questions asked you can go in to your interview with confidence and focus on delivering your responses in a way that demonstrates your ability and character.

Good Luck!