AI News, Data Science Interview Questions

Data Science Interview Questions

is not yet well establish, so interviews for Data Science jobs might include a very broad range of questions, depending on the interpretation of the term by a particular company.

In this post I attempt to organize Data Science interview questions in some usable form, but it might also be biased by how I see Data Science myself.

Don’t let this list of questions discourage you if you don’t know the answer to some of them: chances are that these questions are not important for your interview.

All Machine Learning, Data Mining and Data Science projects should follow some process, so there can be questions about it: CRISP-DM defines the following steps: So next you may discuss each of these steps in details

In my opinion, it's always better to know the underlying theory when talking about Machine Learning algorithms, but your interviewers may have a different point of view.

It also may be useful if the company is doing some marketing or website optimization, so they could ask about related concepts such as A/B tests.

It may be a few basic questions, but it’s helpful to be prepared to more in-depth Machine Learning questions, especially if you claim to have worked with it on your CV.

So you may get the same type of questions as for any software developer position, but possibly with lower expectations on your answers.

was a Java developer for quite some time, and I prepared a list of questions I asked (and often was asked) on Java interviews: Java Inteview questions.

Also, many interviews have a part which I call “hands-on”: you are given some problem description and you are asked to solve it.

For example: Assume that you are asked to lead a project on churn detection, and have dataset of known users who stopped using the service and ones who are still using.

Update: I'm very pleased that this post is getting popular, but some people started copying the questions from here to their blog posts without proper attribution.

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