Witad Awards 2021: Rising star (vendor)—Sophie Chen, Nasdaq

Striking a balance between technology and business can be an arduous task, especially when technology is constantly evolving. Capital markets firms have been quick to catch on—some quicker than others—that throwing technology at a business problem won’t solve anything. 

As a senior data scientist at Nasdaq, Sophie Chen learns about clients and delves into various business topics, allowing her to expand her business acumen. “That ultimately helps me understand business needs and develop data and machine intelligence projects that will solve a business challenge. It’s continuous learning, so you never get bored,” she says.  

Since joining Nasdaq in April 2018, Chen has worked on machine intelligence initiatives from the research and ideation phase, to analyzing and building data models, and then translating those models into tangible business solutions. Working within Nasdaq’s Machine Intelligence Lab, she communicates with business leaders and identifies business problems that can be solved by building and applying new data models. “We start with mapping their pain points, so everything we do is rooted in the business need and the business impact. It’s quite an iterative process of having a dialogue with the business and going back to the drawing board,” she says. 

A mentality that drives her work is balancing perfection and time, especially when prioritizing between deliverables. “From a researcher perspective, I didn’t want to hand anything over until it is perfected. But I learned that you may think that something is critical from your perspective, but it may not be as important for the client. So figure out the priorities, have a stop criterion for yourself, and balance time vs. perfection,” Chen says. 

Chen also echoes what she often hears from her manager: “Good results are better than bad results and bad results are better than no results, because they give you insights on where to go next and how to move forward,” she says.