Unfortunately, on this occasion, your application was not successful, and we have appointed an applicant who…

Sounds familiar, right? After all of these gruelling hours that I spend on the interview preparation, the rejection came after the rejection. Although I was passing the first few interview stages, it didn’t go that well for me during the face-to-face stages. “What a spectacular failure I am”, I thought.

I started looking for ways to improve. I’ve identified a few areas that are usually overlooked but can potentially have a _huge _impact on what will be the interview outcome. This, in turn, helped me to improve and get a job that I wanted to have!

Get The Basics Right

Photo by Clay Banks on Unsplash

The DS internships are usually quite competitive and any red flag for the recruiter might decide if you are rejected straightaway. One of these red flags is whether your foundations are good enough. Data science is a field where you are required to have good mathematical and programming knowledge.

How can you improve? For data science theory, I recommend getting a good mathematical understanding of the most common algorithms. There are two books that I usually recommend: Pattern Recognition and Machine Learning, and First Course in Machine Learning. Both of them contain in-depth mathematical explanations of machine learning algorithms which will help you smash DS interview questions to pieces!

Depending on the company, you might be also asked programming questions. They are often not that hard but given the stress and time constraints, you really need to master them as well. You should expect any questions from sorting, recurrence, to data structures. It’s good to start practicing these questions as soon as possible. To get a good understanding of how to approach the coding questions, I recommend going through the Cracking the Coding Interview book. To get more practical experience, visit the Hackerrank, or LeetCode.

#internships #interview #towards-data-science #data-science #prepare #data analytic