Twenty-nine-year-old data scientist Shivani Patel says her job is perfect for math lovers.
She has always been a math lover herself, but she didn’t originally pursue a degree in math.
“I actually did my bachelor’s in speech and hearing sciences and thought I’d be a speech language pathologist,” she says.
However, when Shivani was working on her honors project, she realized that as much as she enjoyed learning theoretically about speech language pathology, she didn’t enjoy the clinical work she was doing.
“So I took a leap of faith, went back to basics, and decided I was going to do a post-bachelor’s in math,” she explains. “I had always loved math, and while I wasn’t exactly sure what my next move was going to be, I knew I wanted it to be related to math and tech.”
Interestingly, Shivani says it was her Girl Scout experience that got her to where she is today. Her job is at SAP Concur, a company in Bellevue, Washington, that provides travel and expense-management services to businesses. There, Shivani focuses on building machine-learning algorithms.
“When I was questioning a lot in life, Girl Scouts grounded me and helped me work through things,” says Shivani.
Starting in fourth grade, Shivani was very active in Girl Scouts—her robotics-focused troop was one of the first all-girl robotics teams in the country, thanks to a NASA grant, and she earned her Gold Award during her senior year of high school.
“I always had my Girl Scout experience in mind when I was considering what I was going to do for a career,” she says. “When I decided to change my career trajectory, it played a part. Thanks to Girl Scouts, I was more aware there were options in technology.”
She also knew that she needed the right skills to make this career switch.
“To work in tech, especially in my line of work, you definitely need to be able to efficiently teach a computer to do math,” she says. “The better you are at programming, the easier this job will be. Understanding basic math and statistics and how these algorithms are implemented is crucial too.”
You also have to be curious with a capital C, she says.
“To get a job in STEM right now, we’re looking for candidates who display a natural curiosity. We’re looking for people who are willing to ask questions like ‘Why is this done this way?’ We need people to ask questions. So if you have this innate sense of curiosity as well as the necessary programming skills, a career in the data sciences might be just right for you.”
In the end, Shivani is sure of one thing: women are needed for STEM jobs.
“Right now, one of the biggest challenges is for the voices of women in STEM to be heard,” she emphasizes. “That’s difficult because there aren’t enough of us. In AI especially, there’s a negative impact of having people creating algorithms with the same voice. For our field to be the best it can be, we need more women of color and women from all walks of life who are underrepresented to bring diverse opinions—and talents—to our field.”