7 types of Data Science interviews you should be prepared for

Product Data Science jobs are in high-demand. Despite the difficult job market, there are many Product Data Science openings right now. Meta, TikTok, Spotify and Coinbase… are among the many companies hiring for Product Data Scientists.

Over the years, I have interviewed for 20+ Product Data Science roles, and received offers from Meta, Google, Spotify, Airbnb to name a few. Here are the 7 types of interviews (and practice questions) you should expect to encounter.

Looking for sample answers & frameworks for these questions? Check out my Product Data Science Interview Guide here.

1. Product sense interview

These interviews are aimed at understanding how you would approach a real-world problem as a Data Scientist on a product team. They typically come in the form of a case question.

2. Metric definition interview

Metric definition questions are, as the name suggests, about defining metrics. For example, interviewers could ask you to come up with metrics to measure the success of a product feature, or to size the opportunity of a new market.

3. Metric investigation interview

Metric investigation questions are designed to assess your ability to get to the root cause of a metric movement, and to recommend next steps based on your findings.

4. Statistics interview

These interviews assess how you apply your statistical knowledge in a product setting. Check out this list of Statistical concepts you should know as a Product Data Scientist.

5. Experimentation interview

These interviews are aimed at testing your understanding of experimentation principles, and how to apply it in a Product setting.

6. Coding interview

Don’t be fooled by the name of this interview. This isn’t just about your coding skills, but also an opportunity to demonstrate how you combine your data skills with business sense. These are typically done in SQL & Python.

7. Behavioral interview

Behavioral interviews focus on your past experiences and how you've handled specific situations. Be prepared to discuss your problem-solving approach, collaboration skills, and ability to learn from failures.

Looking for sample answers & frameworks for these questions? Check out my Product Data Science Interview Guide here.

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