Niharika Sharma is a Senior Software Engineer for Nasdaq’s Machine Intelligence Lab. She designs systems that gather, process and apply machine learning/natural language processing technologies on natural language data, generating valuable insights to support business decisions. Over the past years, she worked on Natural Language Generation (NLG) and Surveillance Automation for Nasdaq Advisory Services. We sat down with Niharika to learn more about how she got her start in computer science and how she approaches challenges in her career.
Can you describe your day-to-day as a senior software engineer at Nasdaq?
My day-to-day work involves collaborating with Data Scientists to solve problems, ideating business possibilities with product teams and working with Data/Software Engineers to transform ideas into solutions.
How did you become involved in the technology industry, and how has technology influenced your role?
My first exposure to Computer Science was a Logo programming class that I took as a junior in high school. After that, I took a couple of coding classes for fun.
When it came to choosing a college major, my high school Mathematics teacher suggested I consider a career in Software Engineering. At first, I thought, “Programming?! That’s too geeky!”. I liked coding, but I never wanted to be that nerd who sits in a cube staring at a computer all day. For college, I chose to study Chemistry at Delhi University, but a few months into the course, I realized technology was where I belonged, and I eventually pivoted to Engineering.
A decade later, I admit that it was the best decision I ever made. I found the concepts and problem solving so engaging that after obtaining my degree, I took a leap of faith and moved to the U.S. to pursue a Masters in Computer Science from Northeastern University. In the final semester, I took courses in Machine Learning (ML) and Natural Language Processing (NLP). As the semester progressed, I became deeply fascinated with both. By the end of my Masters, I knew I wanted to work on problems related to NLP. Fortunately, I landed an amazing job at Nasdaq right after college. It turned out to be exactly what I wanted to be doing with software!
Throughout your career, what challenges have you been presented with that you’ve had to overcome?
Other than the challenges of moving to a new country and starting a career, an obstacle I had to overcome was to be patient with myself while learning. I can be hard on myself at times, which leads to me being self-defeating.
I used to think if I didn’t understand a concept the first time around, it was because I was not smart enough. Now I realize that learning is a process. It takes time. It’s important to give yourself a break and move forward, knowing that what you learn each day takes you a step further than you were the day before.
I remember when I started my co-op at Boston Fed and got a project that I had no prior knowledge of. It was hard to believe in myself since everything was new, and there seemed to be so many things to learn. I overcame the initial panic and fear by setting small milestones and focusing on a few things at a time. The most important first step is always being willing to try.
What advice would you give to young professionals who aspire to be in the technology industry?
Computer science is an incredibly broad field, and not every language, application or company will suit your interests or support your ambitions. Explore what is out there and find what fuels your passion.
Be a continuous learner. Be inquisitive and always willing to reinvent yourself, adapt and change.