Romane Goldmuntz graduated from Solvay Brussels School of Economics and Management in Belgium with both a bachelor’s degree in business engineering and a master’s degree in business economics, and worked as a technology analyst with Accenture for two years before enrolling in the M.S. in Data Science program at Columbia University. We caught up with the 2021 alumna, who is currently a data scientist at PepsiCo, to learn more about her interests and her Columbia experience, including her internship with Moderna during the coronavirus pandemic.

How did you become interested in data science?

Data science is an engineering field that requires creativity. You cannot be a great data scientist by only mastering theories, algorithms, and programming. You consistently have to read, invent and experiment to achieve the best results. Each solution is heavily dependent on the data you are working on, making each problem a unique brain teaser that is never completely solved. It offers endless possibilities and learning opportunities. It is also a very social and collaborative field, where bouncing ideas with each other leads to greater achievements. Data science is fascinating, and I doubt I will ever be tired of it.

How did your experience at Solvay prepare you for Columbia?

My undergrad covered the [M.S. in Data Science program] requirements in linear algebra and statistics, but the most valuable lesson I learned from my years at Solvay goes beyond technical skills. It occurred in the one computer science class I had during my sophomore year. After a two hour introduction to Python, we were asked to develop a multiplayer version of the game Snake in a team of three. We had 48 hours, no programming experience beyond this two hour introduction class, and the standards were high. We had to meet a set of requirements to get a grade of C, and if we wanted a higher score, we had to overdeliver. Computer science teaching assistants were present in the room, and we could ask them questions, but they would take notes of what we asked, how we listened, and how we implemented their answers. All of these would, of course, impact our grade. This was a hard and challenging experience, but it taught me to remain calm and resourceful in a high pressure environment. By the end of the 48 hours, I hadn’t become an amazing developer, but I had learned to value teamwork, resilience, and perseverance, and these were my key allies when I joined the M.S. in Data Science program at Columbia.

Why did you choose to come to Columbia to study data science?

Columbia has an incredible curriculum that not only covers the basics of data science, but it also offers great freedom in the choice of electives. It gave me the opportunity to take a great variety of classes and to try out several industries in which data science could be applied. This helped me a lot in targeting the right companies during my job search. Another important aspect, which I wasn’t aware of before, is the quality of the student affairs department. Brianne, Violet, and John are a precious resource and a great asset. They help students on so many levels, whether it is related to internship and job search, academic topics, and much more. I’m very grateful to them, and I think that we all are.

How did the pandemic impact your experience during the M.S. in Data Science program?

The pandemic definitely changed our student life, but I feel like Columbia handled the transition very well. I don’t think that the quality of the classes I was taking were impacted by the virtual situation. Covid-19 had way harder consequences on our social lives. I am lucky enough to have family who took me in during most of the spring and summer of 2020, but a lot of my friends suffered from the lockdown situation in NYC. We tried to organize games and call each other regularly, but it wasn’t the same.

Tell us about your summer internship with Moderna.

It was a wonderful experience. I learned a tremendous amount about the use of data science in clinical trials, and I was surrounded by brilliant mentors. Being part of this company in the middle of the pandemic, while it was working on developing a vaccine, also made my work incredibly meaningful.

What are you currently working on and most passionate about?

I’m very interested in the relationship between data science and discrimination. My current personal project revolves around this issue. Beyond data science, I’m involved in several mentoring initiatives. Right now, it is at the data science level, but I’m currently doing research to get more involved in initiatives that are looking to increase the presence of women in STEM.

— Sharnice Ottley