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Women in Data Science Worldwide - Sonu Durgia | Optimizing the Online Shopping Experience

Sonu Durgia | Optimizing the Online Shopping Experience

11/26/18 • 28 min

Women in Data Science Worldwide

Consumers know Walmart as a retailing giant that has changed the face of retail in communities across America. But with a data store containing billions of queries and items, it’s also a laboratory for the company’s data scientists and IT professionals who mine and manage it. “We have data scientists embedded in every single team within the company,” says Sonu Durgia, group product manager for search and discovery at Walmart Labs. “Every function at Walmart, from the quality of groceries to the supply chain, has data science embedded in it,” she noted during an interview recorded for the Women in Data Science podcast at Stanford University.

Because Walmart’s product catalog is immense, holding the attention of consumers and helping them find what they want to buy is a challenge. “We do not have your attention for the next several hours. We have to show you the right things very, very quickly. So it's a ranking and relevance problem right there, even though it's not coming from a query,” Durgia says.
Explaining the insights of data scientists to the business and retail sides of Walmart, people who are not always conversant with technical issues is an important part of her job, she says. Her varied career path has provided her with the expertise to interact successfully with Walmart’s line of business executives. “My engineering degree gives me those tools to really understand the (algorithms) and work with these engineers and very savvy data scientists. My finance background gives me that bird's eye view, understanding what the key things are here,” she says.

Because data science is still a male-dominated discipline, finding a role model can be difficult for women in the field. But technology, says Durgia, has enabled new ways for women to find role models. “Back in the day, you would just look at your peer group to find inspiration or even to solve some problems, ask about a concept you didn't get in class. But now YouTube is your teacher. Everything is available,” she says.

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Consumers know Walmart as a retailing giant that has changed the face of retail in communities across America. But with a data store containing billions of queries and items, it’s also a laboratory for the company’s data scientists and IT professionals who mine and manage it. “We have data scientists embedded in every single team within the company,” says Sonu Durgia, group product manager for search and discovery at Walmart Labs. “Every function at Walmart, from the quality of groceries to the supply chain, has data science embedded in it,” she noted during an interview recorded for the Women in Data Science podcast at Stanford University.

Because Walmart’s product catalog is immense, holding the attention of consumers and helping them find what they want to buy is a challenge. “We do not have your attention for the next several hours. We have to show you the right things very, very quickly. So it's a ranking and relevance problem right there, even though it's not coming from a query,” Durgia says.
Explaining the insights of data scientists to the business and retail sides of Walmart, people who are not always conversant with technical issues is an important part of her job, she says. Her varied career path has provided her with the expertise to interact successfully with Walmart’s line of business executives. “My engineering degree gives me those tools to really understand the (algorithms) and work with these engineers and very savvy data scientists. My finance background gives me that bird's eye view, understanding what the key things are here,” she says.

Because data science is still a male-dominated discipline, finding a role model can be difficult for women in the field. But technology, says Durgia, has enabled new ways for women to find role models. “Back in the day, you would just look at your peer group to find inspiration or even to solve some problems, ask about a concept you didn't get in class. But now YouTube is your teacher. Everything is available,” she says.

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undefined - Megan Price | Data Science and the Fight for Human Rights

Megan Price | Data Science and the Fight for Human Rights

Data scientists are involved in a wide array of domains, everything from healthcare to cybersecurity to cosmology. Megan Price and her colleagues at the Human Rights Data Analysis Group (HRDAG), however, are using data science to help bring human rights abusers to justice.

The nonpartisan group played a key role in the case of Edgar Fernando García, a 26-year-old engineering student and labor activist who disappeared during Guatemala’s brutal civil war. Price, the executive director of HRDAG, says the investigation took years, but their work led to the conviction of two officers who kidnapped Garcia and the former police chief who bore command responsibility for the crime. “It was one of the most satisfying projects that I’ve worked on,” she says. Price discussed the case in more detail as well as other cases she’s worked on over the years and the role data science played in an interview recorded for the Women in Data Science podcast recorded at Stanford University.

For a recent project in Syria, Price’s group used statistical modeling and found information previously unobserved by local groups tracking the damage caused by the war. Similarly, in Mexico, she expects HRDAG to gain a better understanding of in-country violence by building a machine learning model to predict counties with a higher probability of undiscovered graves.

Price hopes that in the future human rights and advocacy organizations will have their own in-house data scientists to further combat social injustices around the world, and she believes that data science will continue to play an important role in the field. She advises young people entering the field of data science and social change to learn a programming language, pick an editor and find mentors and cheerleaders to help them along the way.

Next Episode

undefined - Elena Grewal | From Education to Head of Airbnb Data Science

Elena Grewal | From Education to Head of Airbnb Data Science

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.

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