Placement season is like GOT, you never know what will happen in the next episode. Sometimes it’s quite random. But if you apply pragmatic approach you might find some spoilers :P

My first advice is that give your best, and do not get disheartened. This is just a beginning of your professional career.

Placement process has two parts. First, you need to give a test to be shortlisted for an Interview. This test is generally basic coding+ Aptitude test (for IT field) and core questions (for others). So, it is must that you learn coding, if you decide to go for an IT company. (be it SDE, Data Science or Analyst)

I was shortlisted for four Interviews, out of which I had PPI (Pre Placement Interview) in two. For the interviews, be clear about what you are interested in. I was shortlisted in Citi Group. Interviewer asked me questions on Data Structure and Algorithms. I am not good in this, so I requested him to ask me about Machine Learning (after all that’s all it was on my resume). The profile offered did not require any ML knowledge. I was out of the room in five minutes, but believe me I didn’t feel bad about it at all. The next morning I got an offer from ZS. So, be patient and wait for an Interview where you need to hit hard.

For ZS, I had three interview rounds (I had a PPI in this, so no test). First round was technical. Interviewer was a Manager of Data Science team. He asked me about my internship (I did my intern in Data Science). I described my work and things I could complete and the ones I could not. And then he started grilling me on my Machine Learning knowledge. The questions were not that hard but you need to understand ML basics very well. We had conversation for an hour starting from Logistic Regression to Convolution Neural Nets.

The next round was practical implementation round. Interviewer (he was a member of Advance Data Science team) gave me a dataset and I needed to analyze it in half hour. I did my best with different strategies on imbalanced handling, missing value imputation, feature engineering and selection, model selection etc. Then we had discussion on each of this for half an hour. Here, your EDA skills are tested. The one key thing about interview is “never lie”. Be confident to say “NO” if you don’t know something.

The last round was HR. He asked me about my interests and motivation for Data Science field. When you are a student from non-circuit branch you need to find a solid reason that why you are not pursuing career in your core field. So, give them your true motivation. It need not be any big project, but be honest in this.

How to prepare for DS Interview:

Astute understanding of ML is a must. Participate in various competitions to get understanding of EDA and ML model selection. You need to give your time to crack an Interview. For the beginners, read this great post by Akhil Gupta.

All the best for your future endeavors. Hit ❤ if this was worth a read for you!