If you just got the interview invite for your dream data science job, you probably did two things: 1. celebrated, and 2. went into stress mode.

Fortunately, you are not the first person ever to go through the data science interview process, so you can learn from your predecessors. While any interviewer might throw you a curveball, there are ways to prepare.

First up, 10 questions you should expect during the interview. Then we’ll share some must-know tips to ensure you’re walking out with a job offer (or at least a ton of experience for next time).

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10 questions to expect during the interview

Time to do your homework. Use this list of potential data science interview questions to prepare. This doesn’t capture every possible scenario, but if you can answer all of these clearly, you’ll be in good shape to respond to anything your potential employer throws your way.

  1. Describe one big project you’ve worked on in the last year.
  2. Name one data scientist you admire.
  3. What do you love most about your job?
  4. How would you describe data science to someone outside the field?
  5. Describe your favorite method for data cleansing.
  6. Explain cross-validation.
  7. What is the difference between supervised and unsupervised learning?
  8. Define selection bias.
  9. How would you define covariance and correlation?
  10. Describe overfitting and underfitting, and offer one possible solution.

Preparing for your interview

Here are a few more tips so you can prep now and when the time comes, you can focus your energy on remembering everyone’s names.

Types of interview questions

Your interview questions will fall into the following categories:

All of this information is important if they’re considering you for a full-time data science position. When your interviewer asks a question, even if it seems obvious or irrelevant, try to figure out which category it falls into and what they’re trying to learn about you.


Anything we missed? Share the toughest question from your last data science interview by tweeting @thinkful.

And when you feel ready to nail the interview, make sure you’ve also done these four things to launch a career in data science.

Artwork by Rachel Knobloch.


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