DSI Alumni Download: Q&A with Gerardo Antonio López Ruiz, Research Scientist at MarketAxess
Gerardo Antonio López Ruiz studied applied mathematics at Instituto Tecnologico Autonomo de Mexico, where he first discovered data science. After graduating, he worked as a data scientist for Walmart in Mexico and created a machine learning program to reduce the number of retail products placed on clearance by predicting the demand for each product as well as its optimal price. It was a deft use of data science and he was eager to learn more.
Ruiz recently graduated from the master's degree program at the Data Science Institute at Columbia University and has accepted a research scientist role at MarketAxess. The company, which is revolutionizing how bonds are traded, recently made it onto the S&P 500. Here, he talks about his journey from Mexico to Columbia to a firm transforming the financial sector.
Tell us more about your role at MarketAxess.
As a research scientist at the MarketAxess headquarters in New York City, my job will be to assist the research and development team by helping them develop insights from the data obtained by their trading platform. Those insights could also eventually become services for either the company or the company's clients.
Which data science skills will you use most at your new job?
Machine learning, statistics, and databases will probably be the skills I draw upon most. I have to be capable of understanding the business needs and how to use their data in order to create value.
How did you get into data science?
It was back in my third semester of undergraduate school. I had to recreate a simulation of forest fires and I stumbled upon an article about neural networks and what they can accomplish. I immediately became interested in the subject. It felt like it was exactly what I wanted to do with my degree.
Why did you choose to attend the Data Science Institute at Columbia for your master's degree?
Studying at one of the best universities of the world was a personal goal I have had since I was 15. When the time came to start applying to graduate schools, I looked into every data science degree program I could find. The professors, location, and courses given at Columbia’s DSI made it my first choice.
Can you describe a highlight of your DSI experience?
My favorite class was Applied Machine Learning taught by Andreas Muller. It was an amazing course and it enabled me to vastly improve my machine learning skills. Furthermore, my favorite project was the capstone project. In collaboration with Microsoft Research, we presented a system for cluster-based news classification. I believe the friendships I developed within the program were the highlight of my master’s degree. I was lucky enough to find an incredibly talented and multicultural group of friends who will remain with me much longer than any course.
Do you have any advice for students thinking of studying data science at Columbia?
School is very important, but if you are [considering Columbia], you probably know that already. It’s the networking opportunities at Columbia that will probably get you the dream job you are thinking about. The career fairs DSI runs are great ways to network with many company recruiters and I obtained my job through one of the fairs. So make friends, enjoy the city, and network! A master’s degree is important if you want to advance in your career. Since data science is a field that is constantly changing, there is so much you can learn from pursuing a data science degree. A degree from a university like Columbia will validate your skills anywhere in the world, opening the door for endless job opportunities.
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