Every data science interview is different - but you can expect most interview questions to come from a specific list of question types.

We’ve mapped out what frequencies to expect of each question type based on the feedback from data scientists we work with:

Overall, the most frequent questions are on SQL (in more than 90% of interviews) and machine learning (85%+). Python questions are a close third, asked in more than 80% of data science interviews. Presentations and whiteboarding coding questions are encountered less frequently but still occur in the interview process.

We can classify data science interview question topics into three big groups.

Each of them evaluates different skills. We’ll analyze each group more deeply in the following lessons:

• Coding skills for data science: These evaluate your experience with the languages you’ll need to use to apply any statistical or technical knowledge.
  • SQL Questions
  • Python questions
• Data science technical knowledge: These evaluate your familiarity with the main theories that form data science.
  • Machine learning
  • Probability
  • Statistics & A/B testing
  • Database design & engineering
• Applying data science knowledge: These evaluate your ability to apply data science concepts successfully in real-world scenarios (or within the context of the company that is hiring you).
  • Business cases
  • Applied modeling
  • Product metrics & product analytics
  • Data science behavioral questions

How To Study for the Interview?

Given this wide breadth of topics, how does one study everything?

Simply put, you don’t. Here’s what you do instead:

Ask the Recruiter

If you actually have the interview scheduled, reach out to the recruiter and ask them what kind of questions will be on the interview. Not the company interviewer but the recruiter. The recruiter wants to help you and see you succeed! I cannot stress how easy and beneficial this task is.

In the worst case, they say no. Best case, they tell you exactly what’s going to happen in the interview because, newsflash, the recruiter gets paid when you get the job. Remember, the goal is to narrow the breadth of topics that you have to study, allowing you to go deeper into the subjects that matter.

Read Interview Experiences

If you’re not at the interview stage yet, you can start preparing by doing research, reading job descriptions, and finding interview experiences from other candidates on Blind or Interview Query. Look out for common subjects; if they talk about A/B testing or Python experience in their roles and responsibilities, that will likely be part of the questioning you will receive in the interview.

At Interview Query, we provide an exhaustive list of company guides where we’ve already analyzed which topics are asked for different roles. We also have in-depth guides for companies like Meta and Google.

In the final module of this course, we will provide a more extensive list of recommendations on how to prepare for the data science interview process.