In today’s Accredian Success Story Series, we feature Sohomjit Ganguly, Data Science Consultant, TCS. Sohomjit was a part of Accredian’s Global Certificate in Data Science & AI program, April 2019 cohort.
Sohomjit answers our questions on how he transitioned to a Data Scientist role after more than 7 years of work experience, the selection process, Data Science interview questions asked at TCS, the challenges he faced, and how he overcame them.
Sohomjit’s Data Science story will surely leave you inspired and motivated to pursue your dream career today; as it’s never too late to learn. Read the excerpts from the interview below.
Q1. Tell Us About Your Current Role and Background
I’m presently a Data Science Consultant working with Tata Consultancy Services. I joined this company 9.5 years back. So, within the next year, it will be a decade of experience for me in this company.
My last job profile was that of a Data Scientist and before that, I was working as a Senior Data Engineer in TCS for a different project.
Q2. Why Data Science?
So, switching to a Data Scientist role was a very organic one for me. I was very interested in data, I have seen data at work. And for that reason, I did my MBA in business analytics. And as a business analytics MBA student, I had seen the wonderful ways in which data was impacting businesses worldwide and I was immediately drawn to it. So that is the reason I decided that I would become a Data Scientist one day.
I started my research, checked places, and made connections with credible people who can give me a viable scenario of the market and the opportunities. This was important because I was already having seven and a half years of experience when I wanted to switch to a Data Scientist role.
Q3. Why Did You Join Accredian Data Science Program?
So even after my Master’s in business analytics, I realized that the practical side of approaching and handling data was missing because it was all very theoretical.
I didn’t know what the actual market was, what tools people were using in day-to-day activities. And I wanted hands-on experience on that.
And that’s when I got introduced to a wonderful beginner’s session at Accredian. I did not understand a lot of it, but it drew me, and then I thought that I had the confidence of committing to the program. It was an important factor because there were so many things, the assignments, the studies, and the weekend classes along with my regular day-to-day office activities. So I was committed not only in terms of money, but also my time, focus, and energy.
I made the decision based on that class and the beautiful lectures that were given. My intuition was that this is going to be good. And I can tell you that it has been very, very, very good.
Q4. What Was the Selection Process at TCS?
The selection procedure at TCS was a very, very tight one. There is no shame in admitting that I had given over seven interviews for this position. And in all these seven interviews, I had understood that I lacked what they were looking for.
After seven interviews, I had a discussion with Suchit. And he really refined the process of preparation for me. Earlier, I was preparing and reading a lot. I was doing all the necessary things. But Suchit helped me refine that process of how to gear up for an interview – mentally and from a technical perspective. This shift actually helped me to crack my Data Science interview.
I have told this several times, and I’ll tell it again, the same people who thought I wasn’t Data Scientist material were amazed by my work after I went into this role. So I think it’s about not giving up.
Q5. What Data Science Interview Questions Were You Asked?
Around 40 to 45% of questions in the interview were on Python and its applications. These included questions such as the difference between a list and a dictionary, data frames, and anonymous functions.
The other half of the questions were on Data Science concepts such as supervised algorithms and logistic regressions. I was also asked questions on gradient descent, how it’s calculated, what are the different optimizers used, and the difference between them. So those are very challenging questions. Because if you do not go into detailed studying, then you would find it difficult to answer such questions.
In the end, I was asked questions on the business side. Because, as I told you, I am an MBA, and they were looking for people who can explain the ability of data science or AI models to the customer. So I was asked questions such as how to handle stakeholders, how to plan out data science activity, and how to chart the progress.
Q6. How did Accredian Data Science Program Help You?
Accredian program is one of the sole contributors to my success. I think many factors are underlying that, but I can name a few. One is the wonderful faculty that they have. Second is the very nice and fast responding academic team. Whenever I had a doubt, I would reach out to them and they have always resolved my queries.
The third is specialist support. I remember I had created a kind of GI application in Python. And I asked the academic team to evaluate them. They set me up with a specialist, and he gave me pointers as to what I should and shouldn’t have done, that was insanely helpful for me.
Apart from all these factors, the guidance I have received from Suchit and Manav has been paramount to my success. I think they are industry veterans, they have looked at this industry for a very long time, and they know the ins and outs.
Q7. What Advice Would You Give To Data Science Beginners?
To the Data Science beginners, the most important advice that I should provide is, please be patient. Patience is the key here. When you start learning something, it’s very natural to falter because you don’t know if you’re going on the right track, so it is very important to have patience.
The second important factor is perseverance. If you do not have perseverance and patience, I think you’ll give up everything because everything will sound tough. The third important piece of advice is to stick to your curriculum and practice. I remember that Suchit used to tell us, that if you do not practice, all this will look like a film to you, which you are seeing, and after you close your system, it will become an obscure memory.
If you do not practice, you will not be able to apply what you have learned. And in Data Science, the application is everything. So please keep on practicing.
So patience, perseverance, and practice. Three P’s will always give you an edge over anybody else. Also, keep learning, go through blogs and the latest developments. The faculty at Accredian, always advised us to see new developments and trends, because that is what attracts you into the genre.
I am thankful to Accredian and my wonderful cohorts. I have learned so much from them. I have been in touch with a lot of people who are in a much higher perspective of the corporate infrastructure than me looking at a problem through their eyes, and finding a solution. And their perspective, their understanding has really opened doors for me. Today, I look at a problem from a very, very different perspective.
Hope you found this article useful. If you have any questions related to a career in Data Science, feel free to comment below. We will get back to you.
