At a previous job, Beena Ammanath noticed a trend at her leadership team’s weekly meetings. If the meeting was running late, the CIO would ask her if she needed to leave to pick up her children.
“All of my peers were men, and the CIO was a man,” said Ammanath, who is now the executive director of the Deloitte AI Institute.
“He knew that I had young kids,” she continued. “And I [thought], ‘Why is he asking? I’ve got this covered. I can stay, it's fine.’ I felt singled out.
“But there was one peer of mine who actually needed to leave at 5:30 on Mondays to go pick up his kids because his wife had to work late. He pulled me aside after a few of these instances and said, ‘The CIO really likes you. He's biased towards you.’ And I said, ‘No, I feel the other way, that he's singling me out.’”
This misunderstanding, stemming from a respected leader’s good intentions, was solved during Ammanath’s next one-on-one meeting with her manager, when she told him how she felt — and that another person on the team actually did need to leave earlier. In future meetings, the manager would ask if anybody needed to leave. “Even great leaders have unconscious biases,” Ammanath said.
Ammanath’s experience of being the only woman in the room is not uncommon for women in the data industry — women still hold relatively few jobs in this rapidly growing field. According to a 2020 survey, 27% of data and analytics jobs in the United States are held by women.
During a panel discussion at the recent MIT Chief Data Officer and Information Quality Symposium, Ammanath and other women leaders in the data industry talked about the importance of mentorship, how to overcome obstacles like self-questioning and misperceptions, and the imperative for their industry to embrace diversity.
Make diversity part of your data practice
As more companies roll out artificial intelligence and machine learning capabilities, it’s important that diverse employees are working with the data and creating applications, according to Ashley Van Zeeland, vice president of product integration and customer collaboration at the biotechnology company Illumina.
“It’s almost an imperative, I think, to drive that diversity,” she said. “Diversity from a gender perspective, but also from other perspectives such as age, race, ethnicity, geography, and many others, because we’re seeing AI is such a powerful technology, and we need to make sure it is equitable.”
Companies look for insights from data and how those can be used. “Being aware of how you might be training models based on assumptions that go into how you create applications is really important,” Van Zeeland said. “To make it as equitable as possible, you really want diverse views baked into the use of that data, the collection of that data, from the very earliest stages.”
“As we go into more and more data insights and AI, as we are encoding more of the intelligence, you need those different perspectives,” Ammanath said. “I do think we focus on gender diversity because that happens to be the largest minority demographic.”
Deepa Bajaj, head of enterprise data products and platform engineering at Paypal, recalled a female leader who was the only one on her all-male team to call for a backup plan during a large implementation — another argument for diverse views.
“Diversity of thought is required to solve these big, complex challenges,” Bajaj said. “You need those creative minds, creative thinking, to build end-to-end solutions to solve business needs. I feel bringing more women leaders in the company can help you think differently.”
Find a mentor and build a network
Barbara Latulippe, who leads enterprise data and analytics at Edwards Lifesciences, said mentorship and networking are vital — for example, her company has a “Women in Tech” group that meets once a month.
Only 27% of jobs in the data and analytics industry in the U.S. are held by women.
Mentorship is especially important for difficult social aspects at work, Latulippe said, like company culture and politics. “It’s not always necessarily about navigating the technical aspects of your job,” she said. Bajaj agreed. “Organizational culture and politics is one of the things, no matter how much you study, there's always more to learn and more to practice on,” she said. “Especially when your peers and other leaders around you keep changing — your challenge is, you’re back to square one of learning again. So you need more ammunition in your bucket, more skills to go tackle that problem.”
Relationships with her mentors — including some outside the IT data industry — and with her mentees are equally valuable, Bajaj said. With her mentees, “I feel it's a two-way relationship. I get to learn about them, their backgrounds and their questions, how are they thinking, their strengths, and then they get to learn from me my challenges, how I navigated those situations.”
Van Zeeland said she views her mentors, who are both male and female, as a board of advisors. “Each of us have so many facets,” she said. “There's the part of me that is a woman navigating in a technical field. There's the part of me that was an entrepreneur, the part of me that's now navigating a larger company. Having mentors who can really help in those specific areas, as well as provide an alternative view … is usually valuable as I've gone through my career.”
Don’t talk yourself out of the field
Earlier in her career, Van Zeeland founded a genomics company, aiming to quickly sequence the genome of a young girl suffering from a neurological disorder. “I was a postdoc, I wasn’t a software developer,” she said, so succeeding required building the right team around her. “It was much less about me personally, and more of just figuring out how to fill in my areas where I'm not as strong to accomplish the mission,” she said.
Latulippe said her mentor encouraged her to pursue a job in data science despite her concerns. “I said, ‘Well, I'm not a statistician, I don't necessarily have a data science background,’” she said. “And he said, ‘But you know the business problems, right?’ He was very encouraging. When I started with the team … we focused on solving a common problem, and we all brought our diverse and unique skills to the table.”
She’s since encouraged other women interested in tech and data with similar advice. “You give them the encouragement that they can leverage the skills they have,” Latulippe said. “They don't have to be experts at everything, but they have to have the willingness to learn and the passion.”
“I think women sometimes are hesitant to go for [opportunities] if they don't feel they fit 100% of the skills,” Latulippe said. “But I would really encourage you to take those opportunities.”
“Don't be scared,” Bajaj said. “You can do everything in this world. Go for it.”
Van Zeeland had similar advice for women in the data field.“
Find your mentor, find your sponsor, and if this is your passion area, you can absolutely jump in,” she said. “It's not going anywhere. It's a huge emerging and growing space, and we need more diversity.”