The Data in Beauty: From Columbia Data Science to L’Oreal

While most Columbia MSDS students quickly come to appreciate the beauty in data, the data in beauty is not always so obvious. For Nicole Brye (’25), however, using data to advance research, technology and marketing at the world’s largest beauty company, L’Oréal, has become the start of an exciting new career. She is now part of L’Oréal’s Tech Accelerator—what she describes as “a startup within the big ship”—where she applies data science to challenges that cut across business, research, and innovation.

“Because my team is global and supports all of L’Oréal’s brands, every project is different,” she explains. “One week we’re working with marketing data, the next with lab images. It keeps me learning constantly.”

The ability to move across domains with ease is one of the key reasons that Brye chose Columbia over other master’s programs.

 “I wanted to be mobile,” Brye explains. “I knew that if I have the technical foundation, then I can do anything,” she says. “That’s why I decided to go to Columbia.”

Since joining L’Oreal, Brye has worked on everything from algorithms to predict which items consumers are likely to buy together to  research-and-innovation projects that use computer vision to assess product stability in extreme temperatures. Despite the variety and rigor of her professional work, Brye says, “The transition into industry didn’t even feel like a pivot.”

“Thanks to my training at DSI,” Brye went on, “I already had the foundation, so I could plug in right away.”

From Student to Mentor

While Brye is immersed in the intellectual challenges of her work, she has also stayed connected to her data science roots at Columbia, serving as a mentor for other Columbia data science students through the DSI  Capstone program, where for the past three semesters she has guided a student research team on behalf of L’Oréal. 

“It feels a bit strange to be on the industry side now,” she says. “I remember exactly what it’s like to be in the students’ position, so I try to make the process as smooth and practical as possible.”

Nicole Brye competed with Columbia’s figure skating team while earning her MS in data science.

Beyond what she learned in the classroom, Brye credits her success as a Columbia student and professional data scientist to the resilience and multitasking skills she honed during her years as a student-athlete. A competitive figure skater throughout college, Brye was also on Columbia’s competitive figure skating team through graduation. 

“It’s made me determined and a little bit stubborn,” Brye says of figure skating. The sport also taught her a resilience that translated directly to her studies.

“In skating, if you mess up, there are physical consequences—you’ll hurt yourself. But when I started coding, I realized you can make mistakes and recover—you just run it again. That made me much less afraid to experiment and keep trying.”

Looking ahead, Brye says she’s drawn to work that keeps her building. “I really enjoy developing products,” she says. “Some people go into full management, but I like being close to the code.” Her current role, she adds, lets her do both—contribute technically while shaping projects and mentoring others.

“There’s so much to learn all the time,” she says. “Every project stretches a different part of what I know, and that’s exactly what I wanted.”