Fung Feature: Ilias Miraoui, MEng ’20 (IEOR)
On working as an investment banker, transitioning from social science to engineering, and the role of data and machine learning in markets and beyond
Ilias Miraoui is a new graduate of the Class of 2020 who studied Industrial Engineering & Operations Research (IEOR) within the Berkeley Master of Engineering (MEng) program. Prior to enrolling in the MEng program, Ilias graduated from a dual degree program between Sciences Po & Columbia University studying economics and financial economics.
Here, he shares what inspired him to transition from working as an investment banker to pursuing his master’s degree, as well as his interest in using data to understand and influence markets.
On his educational and professional background
“I grew up between France and Morocco and started my undergraduate studies in a very different field than most of my peers: social sciences. I spent two years in Reims, France — an hour away from Paris and in the beautiful Champagne region — and two years in New York. I eventually graduated from a dual degree program between Sciences Po & Columbia University with a major in economics from Sciences Po and a major in financial economics from Columbia. At Sciences Po especially, my courses were very broad, ranging from comparative constitutional law to sociology.
While I often felt that I lacked specialized knowledge, I loved discovering new fields and working at the intersection of multiple disciplines. It’s the main reason I decided to start my career in the capital markets at TD Securities after my graduation. From my seat in the Debt Capital Markets team, I helped investment-grade corporate clients (i.e. IBM, BMW, AT&T, etc.) raise money on the public and private markets and manage their debt portfolio. I loved getting involved in multiple industries (i.e. I covered Tech/Telecom, Real Estate and Automotive mainly) and being so in touch with the events that shaped our world.
On why he chose Industrial Engineering & Operations Research
Eventually, as I had learned the basics of programming earlier, I was able to automate plenty of the tasks we would have to repeat on a daily basis. Doing so, I realized my limits and how I was missing out on the potential of analytics. I started taking online courses but my investment banking lifestyle (i.e. 8am-10pm on average during the week and some weekends) conflicted heavily with my ability to focus on the subject. I completed ColumbiaX’s MicroMasters program and learned what I considered a tremendous amount already. However, more than ever, I was frustrated and wanted to do more! I created my GitHub and tried to play with NYC Open Data, but I wasn’t moving fast enough. So I took the jump and applied to the MEng program at Berkeley. Given my mixed background and my objectives (i.e. to remain close to the business), the IEOR department was a perfect fit and allowed me to dive deep into the world of analytics.
“I realized my limits and how I was missing out on the potential of analytics.”
On his capstone project
For my capstone project, I worked with Simplr.ai and Asurion (Simplr.ai is incubated within Asurion). We were tasked with improving email cleaners and creating an end-of-sentence completion system for the experts answering customers’ inquiries (a little bit the same way as Gmail completes your sentences when you answer an email). We had fantastic support from our advisors Damien Thioulouse and Clément Ruin throughout the year. We met with them once a week over Zoom and had almost daily conversations on Slack, so as you can imagine the COVID-19 crisis did not impact us as much.
When we started out, the entire team had absolutely zero experience with Natural Language Processing (NLP) and we all learned everything on the go. Before starting our project, we delved into research papers and followed Coursera classes specific to the topic and we were able to quickly catch up thanks to our advisors’ guidance.
On coming into the MEng program with a quantitative background
At the beginning of the program, coming with my finance/social sciences hat, I had a huge imposter syndrome as I was among the rare students in the program that did not come from an engineering major. I had never taken linear algebra before (I highly recommend following Khan Academy’s videos, they are very thorough and easy to follow). I was initially very intimidated by the technical skills everyone displayed and by the fact that some people had already worked in closely-related fields.
As a result, the beginning of the first semester was very hectic for me. I had to make sure I did not fall behind and developed the right bases to delve into the algorithms behind machine learning. It was definitely doable however, and while I wish I had done this prior to the program starting, it only took me a few weeks to catch up to most of my peers on what was relevant for my classes.
On working and learning from data
I am especially passionate about the intersection of data science and finance. I have had multiple side projects beyond the program that attempted to explore the inefficiencies of various “markets.” For instance, in one of my projects, I have been collecting data regarding concerts in most major US cities in order to predict musical events that would sell out. It was fascinating to see how we were able to develop insights and highlight inefficiencies in this market, just a few months into the program. In some other projects, I am trying to highlight how non-optimal odds are in the sports bookmaking market and prices are in the domain name resale industry.
On the future use of machine learning
I believe that machine learning will have tremendous consequences that extend well beyond solving the various market inefficiencies I mentioned previously. I am convinced that for developing countries especially, it will act as an incredibly leveling force. As it becomes more democratized and computing resources continue to cheapen, it becomes ever more accessible for everyone to leverage data and optimize processes. Countries that have the least optimal processes could see the greatest benefits and I hope that in the future I would be able to be part of such a movement and contribute back to Morocco.”
