25 Data Scientist Interview questions and Sample answers.

In this interview training presentation, Richard McMunn will teach you how to prepare for and pass a Data Scientist job interview. Here’s what he covers:
1. A list of Data Scientist interview questions I strongly advise you prepare for.
2. Brilliant, unique ANSWERS to tough Data Scientist interview questions.
3. TIPS on how to STANDOUT during your Data Scientist interview.
4. Further resources (including these slides) to help you SUCCEED!

OTHER USEFUL DATA SCIENTIST INTERVIEW VIDEOS BY RICHARD TO HELP YOU HERE ON YOUTUBE:
Technical Interview Questions & Answers: https://youtu.be/n9baKDP91ko
Google Interview Questions: https://youtu.be/BPm7y0h8KzI
Facebook Interview Questions: https://youtu.be/4hMDN0UAPQ8

COMMON QUESTIONS ASKED ON GOOGLE BY DATA SCIENTIST INTERVIEW CANDIDATES:
How do I prepare for a data scientist interview?
What questions should a data scientist ask?
Why do you want to be a data scientist interview?
What skills are needed for a data scientist?
Questions to crack data science interview pdf?
Python data science interview questions?

25 DATA SCIENTIST INTERVIEW QUESTIONS:
Q1. Tell me about yourself?
Q2. Why do you want to work for us as a Data Scientist?
Q3. Explain to me in simple terms how data science works?
Q4. What are your strengths and weaknesses?
Q5. Lots of users are filling in an online form but then not submitting it. What could the problem be, and how would you use data to establish the exact cause?
Q6. Talk me through the different steps you would follow when starting a data science project?
Q7. What is the selection bias in data science?
Q8. What is LASSO regularization?
Q9. Tell me a difficult challenge you recently had to overcome?
Q10. What would you consider when describing something technical to a non-technical person?
Q11. How would you resolve conflict in a team?
Q12. What do you like and dislike the most about being a Data Scientist?
Q13. What is the bias-variance tradeoff?
Q14. How do you handle tight deadlines whilst working as a Data Scientist?
Q15. Explain the difference between supervised and unsupervised machine learning?
Q16. How do you see future technology advances impacting on your job?
Q17. What is a Decision Tree algorithm?
Q18. Tell me a time when you found a solution to a difficult problem?
Q19. Tell me a time when you were adaptable in a work-related situation?
Q20. Tell me how you’d deal with a client or an internal manager who pushed back on your data science recommendations?
Q21. Why do you want to leave your job?
Q22. Why should we hire you?
Q23. Where do you see yourself in 5 years’ time?
Q24. What are your salary expectations in this Data Scientist role?
Q25. That’s the end of your Data Scientist interview. Do you have questions for the panel?