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How Algorithms Work

Learn cutting-edge skills from the field’s leading practitioners.

Written by Philip Baker
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An IBM employee discusses her background in data science and the illuminating perspectives her coursework in the MScA program has given her regarding her career options for the future.

After an internship with IBM in New Delhi led to a position working at their corporate headquarters in New York, Radhika Gehlot, a second-year Master of Science in Analytics (MScA) student, found herself surrounded by data scientists with backgrounds ranging across the fields of mathematics, statistics, and computer science.

With a BA and MA in economics herself, she had studied much of the mathematics and statistics that served as the backdrop to her data science work at IBM. What was new, however, was how she began to see the ways in which those subjects fueled the algorithms and tools she used each day for her work.

“It was a revelation,” she says. “I hadn’t made the connection before. That’s when my interest in data science really began. I started reading everything I could about the subject, both as it related to my work but also just because I wanted to learn more about it. It didn’t take long for me to realize getting a degree would be the best way to truly learn the depths of data science.”

About Radhika Gehlot

Position
Data Scientist, IBM
Hometown
New Delhi, India
Program
Hobbies
Visual arts

Essential Skills to Succeed

She chose the UChicago MScA program not just because she wanted to learn from leading practitioners in the field, but also because she saw the breadth of its curriculum as ideally suited for her career goals. While she wanted to learn how to code, she also wanted to go deep into other areas of analytics that she knew would be pivotal to her success on the job market.

“I had very little experience with programming before I entered the program, but the courses I’ve taken have given me an excellent foundation,” Gehlot says. “I’ve also deepened my understanding and appreciation for some advanced areas of data science I had not studied before, like neural networks and image recognition.”

“The advantage of being taught by industry leaders is that you’re learning the latest and most important skills,” she adds. “It gives you the confidence to enter your interviews knowing you have what it takes to succeed.”

The advantage of being taught by industry leaders is that you’re learning the latest and most important skills. It gives you the confidence to enter your interviews knowing you have what it takes to succeed.

Radhika Gehlot, MScA '21

Promoting Women in Data Science

As a woman who has already made significant inroads into the male-dominated field, Gehlot notes that she has been the only woman on every data science team she has contributed to so far. What is more, as she has looked around the industry, she has observed how rare it is for women to be in leadership roles as data scientists.

“It’s something that’s particularly true at the larger firms,” she says. “That’s one reason why becoming a data science leader at one of those organizations is a goal I have for my career. But I’m also interested in pursuing my PhD. The courses in the program have sparked my interest so much that I now want to go all the way.”

For the time being, she continues to use the lessons from her courses to expand how she understands her professional work. Her original epiphany holds true, and she continues to marvel at all the ways her earlier education in linear algebra and statistics provides the foundation for the analytics work she does today.

“Compared to when I first started the program, I’m at an entirely different level when it comes to understanding what’s happening inside an algorithm to make it work,” she says. “The MScA program has given me the ability to see the power of the concepts I use in a much more comprehensive way, and it’s opened my eyes to amazing areas of the field I hardly even knew existed before.”

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