Undergraduate Degree: BTech in Mechanical Engineering (minor in Management), Indian Institute of Technology Gandhinagar
Why did you choose the Duke MEM program and your area of study (data analytics)?
I remember watching the MEM video which talked about building T-shaped engineers and that struck a chord. Even during my undergrad, I realized that I wanted to work at the intersection of business and technology and the MEM program was just the right fit. I interned as a business analyst prior to joining Duke and discovered the emerging field of data science. It felt like the natural next step as you need to solve business problems using statistics and machine learning. Hence, at Duke I chose to focus on the Data Analytics and Machine Learning track.
How did the program prepare you for your current career?
As a data scientist at Salesforce, I work on diverse problems ranging from forecasting our quarterly revenue to understanding product adoption and churn. To be successful as a data scientist, besides technical chops you also need to be able to effectively communicate your insights and models to stakeholders. Further, being able to understand the business context always helps to create better solutions. This is exactly the kind of experience we got through the MEM program. I took Prof. Egger’s Data Mining and Opportunities in Big Data courses which had us work on real-world problems and with companies and exposed us to all aspects of being a data scientist.
What were some of the most valuable aspects of your experience at Duke—both in class and outside of it?
Besides Prof. Egger’s courses, Prof. Hopper’s Competitive Strategies course was a really great course. It was unlike any other course I’d taken! Each week he threw an open-ended case at us and we had to do our research and develop an informed opinion on the problem. I still find myself using the “job to be done” framework!
Outside classes, the MEM program has so much going on that keeps you busy and helps in overall development. I was a part of the Consulting Club and CDAR which were a great way to meet more students outside of classes. I specially enjoyed participating in the DataFest, which is a two-day-long data hackathon against 250 students from the RTP area and gave us the opportunity to come up with something cool in a short span of time.
Would you encourage others to consider the Duke MEM data analytics track? If so, why?
For those looking to pursue careers in analytics, I would recommend the Duke MEM program. It’s a great way to get both a holistic education in business and in data analytics, as well as have the option to take courses from schools across Duke like the Fuqua School of Business. The growing community of MEM alumni in various data science and analytics roles proves that employers are looking for candidates with these skills.