Presenting to you the INSAID Spotlight Budding Data Science Leader interview series. This is a series of interviews of budding Data Science leaders, enrolled with INSAID in different courses. These students coming from diverse backgrounds and even different fields, have rich experience in their own domains. They have interesting views to share with the world, their experience in the industry, what brought them to the field of Data Science and many other such interesting aspects. These interviews will enrich the readers about the insights, trends and many other related points.
In a recent conversation, we spoke to Siboli Mukherjee who is enrolled in the GCD program at INSAID.
Name: Siboli Mukherjee
Current Organisation: Vodafone Idea Ltd.
Total Experience: 15 years
Batch: Global Certificate in Data Science (GCD) August 2018
Ankita: To start with, could you quickly walk me through your experience; what has been your educational background and professional experience?
Siboli: I have graduated with a Bachelor of Engineering in Information Technology. After this, I joined Nokia and then Idea; the latter is my current organization. Previously, I was into building solutions and had a brief stint as an Auditor.
Now, I am back to handling the entire network channel in the telecom domain. My complete experience has been in the telecom domain.
Ankita: What got you interested in Data Science and Machine Learning?
Siboli: It all started during my brief stint as an Auditor. In this role, I worked closely with data, dissecting it and reaching the root cause of the problem and then find a solution.
I knew if I had to adopt a statistical method, I need to know machine learning, wherein I could use different algorithms like Linear Regression, Time Series, etc. to detect any kind of abnormal patterns and limitations. Along with this, I was required to make predictions related to my data. All this attracted me to the field of Data Science and Machine Learning.
Ankita: Which is your favorite machine learning algorithm and why?
Siboli: One of my most favorite algorithms is Time Series. I am now into studying deeply about the algorithm to learn its applicability not only in the machine learning part but also with respect to neural networks.
Ankita: What is the goal of Data Science?
Siboli: The goal of Data Science, according to me, is timely predictions to mitigate the risks. This will not only benefit the business but also ensure that the efforts are being made in the right direction.
Ankita: Did you face any initial challenges when you entered the field of Data Science? If yes, how did you overcome them?
Siboli: With humongous data available, working on it isn’t easy and in the process, there might be some instances wherein errors might creep in. The challenge was to learn algorithms and its applications in such a way so as to minimize these errors and implement it to the maximum benefit.
I am learning everything by heart and analyzing it from every perspective. In this process, INSAID has helped me a lot. The way the curriculum is structured, from Term 1 to Term 5, is phenomenal; what you need to do and how is clearly detailed.
I found INSAID is the best, as compared to the other online programs. INSAID’s curriculum is way ahead than what other institutes are providing.
I would also want to mention one of the faculty members here, Birsa. He took classes for Data Visualization and EDA and ML foundation. Decision tree and anomaly detection were few topics that he taught us. The way he illustrated the example of recommendation engine was quite engaging.
Ankita: Are there any Data Science influencers you follow?
Siboli: I’ll name two influencers here. I follow Jason Brownlee and Andrew NG regularly. I want to dive deep into machine learning so I follow these people on a regular basis.
Ankita: At INSAID, students are encouraged to maintain high-quality GitHub profiles. Have you also built a GitHub profile? How do you think this will help you?
Siboli: Having a GitHub profile is very important. I have uploaded a project and am constantly working towards polishing my profile.
I realized the importance of GitHub profile during my recent conferences. Whenever you submit your proposal, they always ask you to share your previous projects. With a look at your GitHub profile, they will know about what all work and innovations, etc. you have done.
Ankita: INSAID’s mission is to groom data leaders of tomorrow; what do you understand by data leaders? And how are they different from Data Scientists?
Siboli: Data Leaders have a road map; a clear vision of what they want to do, say, in the next five years. These are highly knowledgeable people who have a keen inclination towards their domain and are interested in doing a lot for their area of expertise. Data Leaders are the torchbearers.
Data Scientists have a defined kind of work style. They have to provide the outcomes, solutions to the problems at hand.
Ankita: What will be your advice to anyone who wants to start a career in Data Science and who is actually a fresher in this field?
Siboli: First thing is to get a stronghold of the mathematical part, which is extremely important.
Why is this important?
It is because, in spite of there being innumerable packages available, you might need to code. This will be possible only if you are good at mathematics. Along with this, if you can manage to master statistics, it will only benefit you in the long run.
The clearer the concepts, the clearer will be the choice of which algorithm to implement.
My second advice will be- Read, read, read and read as much as you can. You might not get all at once, but gradually you will start picking up and at one point, you will be an expert. Try to implement whatever you are learning and reading. This is the best way through which you can learn and retain it.
INSAID is doing best at clearing the basics to the students and ensuring that they understand it completely.
Ankita: This brings me to the end of the interview. Thanks for the generous words that you spoke about INSAID in this interview. I’ll surely pass it on to the concerned people who are working hard for it. Thank you so much for your time.
Siboli: Thanks, Ankita. Bye!