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 Data Scientist job role you are well prepared for what you might be asked.
The key technical skills for a Data Scientist revolve round statistics and machine learning.
- What is Singular Value Decomposition?
- Why is a comma considered a bad record separator or delimiter?
- What is the difference between interpreted computer language and compiled computer language?
- How do you handle missing data? What imputation techniques do you recommend?
- What’s more important: predictive power or the interpretability of a model?
- Can you give an example of a data cleaning technique that you have used in the past?
- Describe a situation where you had to make a decision between two different types of analysis and why you chose the one you did?
- Could you compare the differences between SAS, Python, R and Perl?
- What is A/B testing and how is it different from usual hypothesis testing?
- What is NLP and how is it related to Machine Learning?
- Do you know what Type-I/Type-II errors are?
- What is the difference between data for usual statistical analysis and time series data?
- How do you identify and overcome obstacles regarding projects, customers and decision makers?
- 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.