Please tell us about your role.

My role involves researching on complex deep learning and reinforcement learning algorithms and techniques and conceiving innovative features and solutions around these technologies.

You have been working in the field of Data Science for quite some time. Is this your passion for domain that drives you? What interests you most about the field? How did the journey begin? What inspired you to get into this field?

I am in this field long before the industry gave it multiple names ranging from AI, ML, Data Science, Advanced Analytics etc. My passion began in mathematics backed analytical sciences from my B.Tech. days, where in a small group we use to practice mathematics based pseudo-algorithmic trading and compare results. It continued during my Navy days, when I started applying similar techniques to inventory forecasting and other Supply Chain optimization domains. Application of such techniques was not very popular in those days, and the consistent domain adaption that I could do of multiple algorithms struck me that I have a natural passion for these. In those times an interest in such techniques was not considered either glamorous, nor trending from employability perspective; in fact the most popular way of pursuing your passion in this area would have been to join either the statistical dept. of Govt., or actuarial dept. of a company.

What do you think are the key skills required to be an ace Business Analytics professional?

Mathematics, Coding, and Passion. If someone tells you otherwise, that is probably marketing.

Can you tell how Artificial Intelligence will play a huge role in businesses in the coming years and how management students can prepare themselves for the same?

We are living in an era where AI algorithms and supported agents have started surpassing human skills in multiple domains. Given their durability, maintainability, and endurance, over human skill/motivation, it seems logical they would start replacing humans in different tasks. A major contentious area in delegating the tasks currently reserved for humans to these agents would be of ‘RoI’ and ‘Responsible AI’.  This emanates both from the policies and the data governing the training and application of the underlying algorithms. We see the roles of management sciences increasing in driving most of these grey areas into either black or white.

How did your one year at Great Lakes prepared you for the corporate world? Any special incident/experience you would like to talk about?

Given my background and motivation towards this area, some find it counter intuitive that I joined an MBA program. But to keep things in perspective, Great Lakeswas amongst the first MBA institutes, especially for executive program, to adopt the positioning of  Analytics MBA (that time Uncle Bala used to refer it as BABI for Business Analytics and Business Intelligence). Coupled, with the fact that I had a natural flare for mathematical and technical application of different ideas, what I was looking for was to develop insights of adopting these for the different challenges in multiple domains.

After my MBA, I completed my MTech. (Data Mining) and am now am in the final stages of my PhD. (AI). The knowledge and skills that these courses generate are now a hygiene factor for my role. Many of my colleagues would possess similar experience akin to these programs. I believe that what gives me a different perspective is my experience in Navy, hands-on experience in Core Industries as an engineer, and my ability to see what challenges any business would encounter and how AI could help create a forward looking solution to such problems.

Many of my inventions and patents have been benefitted from this unique insight and the innovative AI solutions I develop easily resonate with their end-users.

What would be your message for Great Lakers?

An MBA is marketed to teachyou the smart work. The program at GL will go a long way in teaching its smart students, smarter business acumen. The smartness so acquired would help them get a very glamorous title in a high growth industry. But what will help them survive many difficult tides is hard-work and consistency. This aspect is important as I see many newcomers entering into the data science because it is trending and also claims a better pay-cheque. But the area of AI is far from static, and to create a mark in this field one needs to be in a continuous learning mode. One needs to remain curious and learn things even when they do not find an existing application of that new technology in their current work environment. Of course someone who has entered this field just influenced by the current trend and glamour around this would not be able to sustain the curiosity for very long.

This has a significant risk of graduating students not giving enough opportunity to identify what they really like doing over and over again, without being influenced by the current demand of that skill or the pay cheques that it can claim. For a management student this may be a weak risk/inspiration, but if even they want to see them closer to fulfilling the peak of Maslow’s pyramid, now is the time to start influencing their potential role to optimally suit their natural skills. Do not keep an aim to fly higher if you are a fish within; and instead try to find the cleanest water and a peer group that is good and deep.