If you are looking to hire me, this is my professional resume.

Far too often while interviewing candidates, I find myself trying to gleam the story from their resumes. So for this page, I thought, why don’t I give the story myself. Here goes.

2005-10: Electrical Engineering at IIT Madras:

I spent 5 years at IIT Madras, a prestigious engineering school in India, for my Bachelors and Masters degrees in Electrical Engineering. Getting into an IIT was a big goal of mine and thanks to my strong math skills, I was able to crack the entrance exam. My engineering education itself was, unfortunately, not up to a high standard. Despite spurts of interest, I realized that I did not have a real passion for the subject. I did well enough to graduate, spent an interesting semester as an exchange student in Sweden and took the first job I was offered out of college.

2010-14: Risk Analytics at Citi:

For about 3 years, I worked for the Risk Analytics group at CitiBank, North America through a consulting company (TCS E-serve) in Mumbai. My role was mostly in building backend infrastructure to track and report the health of various credit risk models that Citi had deployed around the world. The data was housed in a Sharepoint repository and I used Javascript and VBA to automate the building and distribution of these health reports along with early warning flags.
Though I enjoyed coding and building things, I was more fascinated by the statistical model building process and I felt that it was a better match for my skill and interest. Moving across teams within org turned to be harder than I imagined, so I started looking for hands-on modeling roles outside the company.

2014-15: Analytics Consultant at 247.ai:

I spent an exciting year and half with the text mining team at 247.ai (a customer service company with a heavy emphasis on using data science to propel the business forward). The team's main focus was to utilize the text flowing through customer service chats to improve the quality of service. We built several machine learning models to answer questions like What kind of complaints did we receive today? Can we tell if this person requires help with billing based on his/her browsing history in the last few minutes? Is the customer service agent being polite etc.
We were able to build, deploy and track the results of new models, sometimes all within the span of a week (compared to 6 month turn around times in a bank). It was an eye-opening experience to see the direct and immediate impact that your product has on improving the lives real customers. I would have loved to continue in 247.ai for longer, but due to some personal issues, my wife and me decided to move out of Bangalore to the US.

2015-16: Masters in Analytics at Univ. of Cincinnati:

Though I took up the program mainly as a gateway to the USA, I happened to tremendously enjoy and excel at the courses on offer. The advanced statistics and probability courses that I took laid strong foundation to my hitherto programmer-like approach to analytics. I received several job offers and chose to join a startup named EBTH in Cincinnati.

2016-18: Data Scientist at EBTH:

I spent about 2 (awesome) years at Everything But The House (EBTH), a startup in Cincinnati, which at one point was the most valuable startup in Ohio. EBTH is an online auction platform which connects shoppers and collectors with valuable items in estates (a sort of high-end E-Bay). I was the first data scientist to be hired and I relished the opportunity to build things from scratch, right from the basics like creating a reporting framework, defining key metrics, building visualizations in Tableau to more cutting-edge work like implementing a recommender system and building a deep-learning based image recognition system to identify item category and predict auction price ranges. Unfortunately, the company eventually ran into funding issues and I moved to Quotient in Cincinnati.

2018-Present: Data Science Manager at Quotient:

I presently work at Quotient (formerly coupons.com), a digital marketing company, that helps consumer goods companies and retailers reach the right audiences for their brands through promotions and media. I was initially hired as a Sr. Data Scientist and was promoted in Dec 2019 to lead a team of three data scientists. The main focus of the team is to build custom audience segments at scale and subsequently measure the performance of these campaigns with appropriate statistical rigor.