Common Questions an Aspirant Face in a Data Science Interview

Have you ever thought of becoming a data scientist? It is one of the prestigious jobs and is also considered to be the second best job in America this year. However, getting this prestigious job is not that easy. An aspirant has to undergo rigorous interviews to get employed in this field. Questions asked on data science can be complex and broad. It is because a data scientist has role to play in various sectors. You have to review questions under different categories to prepare yourself for data science jobs better.

Through expert analysis we have listed different categories from which interview questions are asked in data science. They are –

  • Coding
  • Algorithms
  • Probability
  • Business case
  • Technical
  • Modelling
  • Statistics
  • Product
  • System design

Analysis has shown that majority of the interview questions are asked from ‘coding’ and ‘modelling’categories, they are the most dominant ones.In fact, these two are the most crucial skills for a data scientist. Though coding questions consist of 1/3 of the questions, other categories like statistics and algorithms are also significant.

The Categories of Data Science


Coding is the most important segment of data science. These questions need a kind of data manipulation with the help of code. The questions are formulated to test the creativity, problem-solving ability and coding skill of the aspirant. One should write the codes in SQL since it is the most popular tool in data science. There is one concept that is unavoidable in interviews – joins. So, one should have clear understanding of the different joins and their way of use.


Modeling is the second most important sector in data science. Here the questions are framed to test the knowledge of an aspirant in building statistical models. Regression is the most commonly asked question in an interview of data science.


Questions in algorithms require students to solve mathematical problems with the help of code and one programming language. The questions need to be answered in a step-by-step process which usually requires computation or adjustment to get the right answer. Questions in algorithms assess the basic knowledge of an individual about data manipulation and problem-solving. This capability is required for complex problems in real life work.


Interview questions on statistics test the knowledge of the student about statistical theory as well as other associated principles. These questions judge how much familiar a student is with theoretical principles of data science. Therefore, one should have complete knowledge of the mathematical and theoretical background of analyses. When taking preparation for job interview, a student should learn the topics like Bayesian statistics, hypothesis testing, median and mean, the p-value, correlation and covariance, standard deviation and variance.

Asides these categories, there are other sectors which test students about technical concepts, design of technology systems, general business ideas and his ability to evaluate a service or product. Thus, in an interview of data science, all kinds of questions are asked but, some of them have greater importance.

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