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Data Scientist Interviews

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Data Scientist Interview Questions

In a data scientist interview, expect employers to ask questions that assess your data modeling, problem-solving, and programming skills. Be prepared to answer general questions that test your knowledge of statistics and data science. You should also be ready to answer open-ended questions that test your creativity, communication skills, and formal education in data modeling and programming.

Top Data Scientist Interview Questions & How to Answer

Question 1

Question #1: Which data modeling techniques do you prefer and why?

How to answer
How to answer: Turning data into understandable and actionable information is a critical part of the data scientist's job. This question allows employers to understand your data modeling skills and background. List and discuss your preferred data modeling techniques, including benefits such as ease of use, flexibility, etc.
Question 2

Question #2: How would you detect bogus Instagram accounts used for scamming consumers?

How to answer
How to answer: Questions like this one allow an employer to test your problem-solving skills. When answering open-ended questions such as these, feel free to ask clarifying questions and use whiteboards to demonstrate your coding and diagramming skills. Share your thought process as you work through the problem.
Question 3

Question #3: Describe circumstances that require a list, tuple, or set in Python.

How to answer
How to answer: Interviewers will use questions such as this one to test your Python programming skills. Review Python basics such as lists, tuples, and sets before your interview. You should be able to explain when and how each tool is used by data scientists.

54,376 data scientist interview questions shared by candidates

All bases of statistical analysis, machine learning and deep learning including probability, confidence interval, hypothesis testing and frequentist and Bayesian analysis, supervised and unsupervised learning and time series machine learning and time series neural network were discussed. More concepts on big data tools and skills were also discussed including knowledge of cloud services, dockers & containers was also assessed . Other domains of business knowledge such as software engineering, business analysis was also checked upon. A real problem was also discussed to gauge the problem solving skills and see how I would approach the problem.
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Data Scientist

Interviewed at Confiz

4.1★
Feb 2, 2021

All bases of statistical analysis, machine learning and deep learning including probability, confidence interval, hypothesis testing and frequentist and Bayesian analysis, supervised and unsupervised learning and time series machine learning and time series neural network were discussed. More concepts on big data tools and skills were also discussed including knowledge of cloud services, dockers & containers was also assessed . Other domains of business knowledge such as software engineering, business analysis was also checked upon. A real problem was also discussed to gauge the problem solving skills and see how I would approach the problem.

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