Episode Summary

Elena Grewal, Airbnb’s head of data science, discovered the key to making successful career jumps: “Often it’s more about words being different than about skills being different”

Episode Notes

Career paths don’t always follow a straight line. Just ask Elena Grewal, whose education culminated in a PhD in education, but who became the head data scientist at Airbnb.

In some ways, the leap wasn’t quite as daunting as it might sound. Grewal’s training at Stanford was interdisciplinary, including statistics and econometrics. “Often it’s more about words being different than about skills being different,” Grewal said in an interview recorded for Stanford’s Women in Data Science podcast.

At one point, she began to study machine learning and initially thought it was very different from the work she was doing. “Then I started looking at what people do in machine learning, and I was like, ‘Oh, it’s logistic regression, it’s clustering analysis. I do that; we just call it something different,’” Grewal says. Whether it’s called data science or not, many different fields have some kind of quantitative component, and people in those fields who are using quantitative skills may well have the background to become a data scientist, she says.

Employees who are not data scientists can learn to understand and use the data their companies collect. Grewal started “data university” at Airbnb, a program that teaches employees at all levels to work with data to do just that. “I don’t want people who have data to be the keepers of knowledge or power, but to share that and to enable every person to be able to think more critically and to be able to make conclusions themselves,” she says. Grewal’s team taught SQL – a standard language used to query databases – to employees and created a database they could use to access company data. Since Airbnb launched data university last year, hundreds of people from other companies have asked Grewal’s team to help them start similar programs.

Although undoubtedly successful today, Grewal champions the importance of grit and believing in yourself as a student, as she herself struggled academically when she was younger. In middle school, a “teacher sat down with my parents and told us that I was a really nice kid and that I was going to be fine in life, but I was just never going to be a top student,” she says. She didn’t let it bother her. After working intensively on math with her father, a university professor, Grewal’s grades shot up and she graduated at the top of her class. “I think that was an important early experience: Where you are is not where you can be. It’s important to just work hard, do your best, and see where you can go and not feel limited,” Grewal says.

About the Show

Hear from women leaders across the data science profession, as they share their advice, career highlights, and lessons learned along the way. This podcast is brought to you by the Stanford Institute for Computational & Mathematical Engineering (ICME) and the Stanford School of Engineering. Generous support for this podcast and other Women in Data Science initiatives has been provided by Intuit, Microsoft, SAP, Walmart Labs, and Western Digital.