Unveiling Data Science Insights: Conversations with Veer Bhadra Yadav

Unveiling Data Science Insights: Conversations with Veer Bhadra Yadav

Welcome, everyone. I'm Anshika, secretary of the career development wing in Academics and Career Council.
Today we have Veer Bhadra who is successfully placed at Sprinklr.
Hi, Veer! How are you doing?
Hi Anshika!  I'm doing great. In a party mood today as it’s Saturday.
Great. So let’s get started. We will try to explore the stages of your preparation for the data science roles.

Q1. What initially sparked your interest in data science? And how did you decide to pursue it as a career path?
It was only when COVID started, like in 2020, somewhere around the start of our 3rd semester that I realized that it was time to do something. During my first year, I was with the dramatics club and I was just having so much fun, other than academics. So I was very careless about all these things, what will I do and all those things. So later, I realized, okay, let's do something. And then I think we have a course in the first year here on fundamentals of computing. To be very honest, I didn't have any idea what coding was or how we should approach the world of coding before that course because I didn't have computer science in my class 12th. So I was, very much new to the coding and all this stuff. And due to COVID, we did it only half till mid-semester. After that, the course was not completed. Feeling that something was missing, I started on my own to learn to code more. The course we learn teaches C language and my seniors advised me to learn C++. So I started on my own during the summer vacations. But when I did it for two months or three months, I was losing some interest in coding and all these things. While everyone else in college was going on about the need for coding for placements, I was a bit doubtful. So it was around late 2020 when I thought of the idea of doing something different. Every second person on campus was doing SDE. There was some course by the IME department during my fourth semester. It was a short course, mainly 5-6 days on what is data science. So, I just enrolled in this course. Didn’t know what it was. Was just getting going to see what data science is. But yeah, found it interesting, and then I just started from there.

Q2. Can you share some of the key courses or projects during your college years that you found particularly influential in shaping the scale and passion for data science?

I would just get some idea of what data science is and how it works, then read a few books and then I started a project. During the project, I used to study the problem using the internet and all the other sources. So I will say a few courses are very important. First, there is a very famous course by Andrew Ng on Coursera. I think that was developed a few years ago. That is the perfect course for a data science beginner. He just kind of explained everything in a very different and simple manner. So other than that, I prefer books ( it's just a personal choice) books have been better than YouTube because it sometimes distracts. So on YouTube, we do have so many open-source courses. So one can do any other courses from the other open sources. Saying on campus in our academics, we have some courses in the CSE department, like Introduction to Machine Learning. I did that course. But I found it a little bit tough or I would say, the way they present to students is insane as it makes things look very tough. So if a person just starts with the introduction to machine learning as his or her first course in data science, then surely he or she would continue, or would want to continue in that direction. Apart from this, probability and statistics is the most important course to understand data science. And linear algebra, you should be very much aware of linear algebra, because all machine learning models just work on linear algebra.

Q3. What was the typical structure for the interview procedure at the companies and how is preparing for a data science role different from data for a software role?

Interviews are similar to all SDE, you do have some technical rounds, and there is some major takeout, then some HR procedures, generally most of the companies follow the same procedure. And to be specific for Sprinklr, we were supposed to have five rounds, but I had only four. Three were technical rounds. And the last one was the HR round. And in the three technical rounds, they just start with very basics in the first round, they just give up in the second. And in the third, it was like everything that they can ask from anywhere and just dig deep and deep. Each round is eliminating round so they were just digging deeper, deeper, and deeper. And then we have the HR round. It's very company-specific and they ask questions like what are the company values and all those things. So, one should check for the company values before particular tracks around for a specific company.
And coming to the second question, was how it is different the preparation of the SDE role and data science role. So I would say there is one part in common, and that is DSA. For every data science role, I have seen the test, they ask questions on coding. So coding is common in most other roles. Apart from that, in SDE, we have something specific like competitive programming and all those things. But in data science, we don't dig that much deeper. But yes, we should be aware of the coding, at least DSA should be prepared and in the interview, they do ask questions on it. Apart from that for data science, you have to do some special courses, and you should know what data science is. But yeah, there is some similarity also.

Q4. How do you handle time management and paradise tasks when faced with multiple academic commitments or projects?

I think time management should not be a problem, We study at IITK and well we already know how to manage our time. Even from the start of the first year, students very well know how they should give their time to multiple commitments. But I will say that they should have clarity in mind about what they're going to do because if you start this thing, let's say in 3rd year (that might not be late), I would say not do those things. You should start earlier. Because everyone nowadays knows how things happen. So those who start early, obviously have more time.

Q5. Is there any additional advice you would like to share with students who are preparing for job interviews in this field?

It depends on person to person like how they approach me while asking this question. So, I would say first of all that you should know what the company is doing before getting into its interview panel. If in the HR round, they get this thing in their mind that the person they are interviewing, has some idea of what the company is doing then they kind of feel impressed by that person. We have to prove to them how we're different. So, the first thing I would say is to always get to know about the company. Try to talk to some senior of the company who is already built in there because he or she might know better what the company's doing or try to get knowledge from internet resources. Always give your best in all the interviews. Think of each interview as your final one. Think of it like your job depends on it. Apart from this, there is an ideal presence of mind that always matters in interviews.
Thanks a lot, Veer for taking time out of your schedule for this interview. This interview will be shared with the students and will serve as a great guidance for them.