Getting in the Data Science Interview Mode

  1. Reduce the surprise – Research in advance:The hardest part about interviewing is having to think on your feet to get answers while people are looking at you and the clock is ticking.  Even questions you would normally think are easy seem hard in this environment.  Minimize this surprise as much as possible by learning what to expect in each interview and preparing for all the things you know are coming.  Glassdoor has interview reviews from people that have been through it, so don’t take the interview until you’ve done some research and at least read what’s out there.  Always ask the recruiter what you can expect and their advice for preparing.
  2. Have the stories prepared and rehearsed.  You should expect questions that are meant to understand your attitude/character and have already thought out several examples of your past that demonstrate desirable traits. The skill is being able to narrate a short anecdote that has just enough details to set up the narrative and establish you as being the person doing the good thing they asked about.  They’ll ask clarifying questions if they want to, but avoid rambling and giving too much information.  Don’t be a bore!
  3. Practice solving problems, out loud and by writing the solution on paper.  If you’re a Data Scientist, SQL / R / Python / SAS questions are very common. Practice enough to be able to answer the basic questions on the fly.
  4. Problem-solving framework: An approach is much more important than the final solution, so make sure that the framework and the approach are as solid as you can make it. This is something very personal and needs a lot of practice. You can look up at Kaggle and other such platforms to familiarize with the typical practice problems and their forums are an excellent food for thought for different problem-solving frameworks.
  5. Know the basics.  Resources like’s combinatorics pages will give you a refresher on core principles as well as examples to test yourself.  You should expect probability and statistics questions, so don’t allow yourself to waste time trying to remember Bayes’ Theorem when you can prepare for it.
  6. Know the common technical concepts.  If you’re in Data Science, you need to understand bias/variance.  You need to know ways of detecting and handling an overfit model.  You need to know strategies for dealing with classification problems when the classes are highly imbalanced.  You need to know the pros and cons of the various model structures.  You need to also understand the basics of how the algorithms work; what is random about random forests and what is meant by gradient boosting?  Treat the technical interview as an oral, comprehensive final exam.  Learn the core principles of the major concepts.
  7. Know the company.  Spend time thinking about the products of the company, how your job impacts the core of the business, and a few ideas of how you would do your job to solve an important problem. There’s a tremendous amount of information on the web that will help, you just need to be proactive in finding and absorbing it.
  8. Be Human, Be Gentle: Recognize that being technically qualified is only part of it.  People will also give their feedback based on if they liked you or not.  Project a good mood, be flattering to them and their company, demonstrate your excitement with the role and your humility in the opportunity.  Someone is more likely to forgive a small technical deficiency of a person they like than rude behavior of a technically brilliant person.  This is also true of your communications with the recruiter.
  9. Last, truly internalize the idea that a job rejection is not a judgment on your talent.  The odds are that you will be rejected … several times.  But that’s OK because this is a big world and we know it’s a numbers game.  Not everyone is a great fit for every job and team, even if they are technically excellent.
  10. Ask Questions – Show Genuine Interest: You should be interested in the company in general and ask genuine questions (you should have some if you are interested). It is as important a decision for you as it is for the Company which wants to hire you.
  11. Wish you luck with the Interviews!


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