Nikhil Dwarakanath

Briefly, describe your personal and professional achievements (including recent awards/ special projects).
I have over ten years of experience in the Analytics and consulting business. I began my career in 2006 with the Analytics Practice at Genpact, formerly GE Capital International. After almost a 9 year stint at Genpact, which involved core quant problem solving, analytical consulting, and P&L management, I moved to Snapdeal, India's largest pure-play e-commerce marketplace.
Tell us about your profile prior to attending ISB and recap your professional life after ISB, including your career progression.
Prior to ISB, I was the operating lead for teams that worked on core analytics problems in the marketing and operations domains, predominantly for retail & lending institutions. I also often wore the hat of a consultant, structuring analytics-driven value for enterprises in the US, Canada, Continental Europe and Australia. Very shortly after graduating, I moved to Snapdeal. At Snapdeal, I started off as Head of Consumer Analytics where I was involved on projects around clickstream analytics, personalization, the design of experiments & growth hacking. I am currently part of the Central Data Science team and work with leadership to drive data enabled strategy for Snapdeal around Product, Conversions, Consumers & Marketing.
What was the main highlight or most memorable aspect of your programme at the ISB? How do you think your time at ISB has contributed to your career and personal growth?
There were two things that absolutely stood out in terms of my time at ISB - The quality of the faculty and the diverse experience of the class. Learning a wide set of contemporary techniques and collaborating with a bunch of really smart people was a real high point. The pedagogy was extremely rigorous and well put together.

I am happy to say that I was part of the founding class of ISB CBA program.
What is the next new thing in the industry or vertical you are working in? Are there any trends that you can identify?
The advent of large-scale distributed systems, maturing AI frameworks, stream processing, etc., are allowing organizations, particularly internet businesses to rethink conventional model development & deployment. The shift away from sample-based modelling to machine intelligence is becoming very obvious.
If you could offer a word of advice to the current class at ISB, what would it be?
As we get more technically enabled at the science of managing and manipulating data, one piece of advice for the class would be to never forget the principle of parsimony. The model with the fewest variables, the solution requiring the least explanation, the chart that can be understood at a glance, etc., are sometimes forgotten as we tend to revel in the practice of the data sciences.

Published Date: 2016/08/24