AI and Analytics for Business


Working with AIAB: Eli Bernstein

When I first started working as a Research Assistant for AI and Analytics for Business (AIAB), I had no idea what I was getting myself into. At the time, I needed an extra work-study position and when I saw a Wharton research center – and an analytics center, at that — was looking for students to hire, I did not hesitate to interview. After a few basic questions about concepts I did not understand like “SQL” and “data analytics,” I was offered a position that would become one of the defining parts of my undergraduate experience.

It took me a while to realize the richness of the opportunity provided to me. My first assignment for AIAB was to attend a SQL boot camp. It was where I had my first run-in with Structured Query Language, or SQL. At first, I did not understand the point of this language. Everything we did could have been done so much more efficiently in Excel. What was the point of “SELECT customer, product FROM prod_tbl” when I could just as easily execute a “VLOOKUP?” It wasn’t until I started working with larger data sets and answering more complex questions that I could wrap my head around what this “big data” stuff was all about. A year and a half later, I feel as though I have only scratched the surface, but have gained a huge appreciation for the opportunity AIAB offered me.

It also didn’t occur to me until later that as a Research Assistant, my role was to learn one of the most valuable skills in the workplace coupled with working alongside real companies and researchers on problems that lie on the cutting-edge of customer analytics, which is exactly why AIAB exists.

The center is situated between industry practitioners and researchers, AIAB is a conduit for knowledge, learning, and innovation. To be a part of that bridge is an awe-inspiring experience, to say nothing of the skills I have acquired and experiences I have had because of it. After working at AIAB, I have been able to breeze through any interviews that test SQL knowledge, and I have no shortage of stories about how an assignment I worked on impacted companies whose brands are recognized globally. I have worked alongside researchers striving to answer some of the toughest questions in their fields as well as business leaders seeking to shape the future of enterprise analytics. This dual window into both theory and practice has given me the invaluable opportunity to view and understand the interplay between research, innovation, and commercial success.

In a day and age where on-the-job training in technical skills can be difficult to find, AIAB not only provided the resources to learn an important skill, but it made me aware of opportunities that are available to students who seek them out. It has been incredible to watch AIAB expand over the past few years, and I am very excited to see what the future holds for myself and AI and Analytics for Business.