Data science is tough work — but equally rewarding as well.

Data is plentiful, and there are several different specializations for people to choose from, from data engineering to marketing data analysis. Breaking into the industry can be overwhelming, with the several options to choose from and the constantly evolving landscape of technology, but it can be a fulfilling career choice for the right people — including the number of women now becoming increasingly interested in the field.

“I understood how powerful of a role data plays in making informed business decisions,” said Lyla Kuriyan (pictured), managing director of technical professional services and marketing data science at Google LLC. “There’s just so much uncertainty in the problem that we’re trying to address. There’s a lot of ambiguity, and data science is just absolutely critical to helping think through making those decisions and uncertainty.”

Kuriyan spoke with Lisa Martin, host of theCUBE, SiliconANGLE Media’s livestreaming studio, during the Women in Data Science (WiDS) event. They discussed being a data science leader, what career skills are necessary to be in data science, and more.

Applying data to solve problems

As a managing director at Google, Kuriyan and her team are understandably accountable for several critical tasks, working directly with some of the most sophisticated and successful chief marketing officers and marketing organizations in the world.

“Our marketing data science teams measure and optimize … a return on investment for Google’s largest global clients,” Kuriyan explained. “We sit down at the C-level table and … ask a lot of questions so that we can understand the customer’s business objective and how data can help them think through the various options they have.”

Kuriyan also has advice for those seeking a career in data science. Being able to focus on what matters most during complex and ambiguous and multifaceted problems, for example, is a crucial skill to hold.

“Another one is the importance of storytelling. I mean, without a good narrative, it can be hard to move from data to insight, and when you’re faced with lots of data, being able to distill that complex data into a meaningful and coherent and impactful story,” Kuriyan said.

Here’s the complete video interview, part of SiliconANGLE’s and theCUBE’s coverage of the Women in Data Science (WiDS) event:

Photo: SiliconANGLE