How to prepare for a Data Science Interview ? — by

We started this analysis because we wanted to understand how top data science teams interview and how you should prepare for that process. We’ve managed to condense what we’ve learned into six actionable points.

  1. Research research research. Spend the time to understand what the data science team in each organization is working on. You’ll do better in the interview process, and you’ll be able to relate better to future colleagues. You’ll be asked a lot of situational and product questions that have to do with current work the company is undertaking, whether it’s People You May Know with Linkedin or determining how drivers should be matched with passengers with Uber.
  2. Prepare for four categories of data science questions: statistics and probability questions, programming questions, business thinking questions, and culture/role fit questions.
  3. Practice statistical modeling/reasoning, describing machine learning concepts, work in SQL, R, and Python from the basics to more advanced work under time constraints. The data science interview process is pretty standard across companies: phone screens, tests, and then on-site interviews. You’ll want to make sure you come off well in interviews and time-constrained assignments. Practice using SQL, R, and Python under time constraints. A lot of take-home assignments try to catch you by surprise on this and test your familiarity with the languages with very little time. Showing you can think in frameworks like Hadoop at speed is impressive for these hiring companies, but don’t forget the basics too! Sometimes companies will ask basic statistical questions to make sure you’re on top of your game.
  4. Get a referral. Four out of nine companies we surveyed had internal referral as the top source of interviews (Google, Uber, Facebook, Airbnb), and overall, it was the second largest source of interviews. You’ll want to get to know people in the company and get them to advocate for you rather than just applying online.
  5. Prepare your story. You’ll be asked to go over your past work in detail. Be prepared to run over everything you’ve done with as much specificity as possible, from the tools you used, to why you made different decisions. Be ready to weave a coherent narrative of how the amazing things you did improved business outcomes.
  6. Prepare for a long, drawn-out process. Interviewing for a data science position can take months and multiple stages. Make sure you’re ready for the wait.