In 2018, Kishawna Peck was looking for a conference to attend. At the time, the Toronto data scientist was working at a financial technology company and hoping to find an event that focused on women, or at least featured something beyond panels of all-male speakers. There was nothing.
“Maybe I can do it,” she thought to herself. Over a six-week period, Ms. Peck and some friends put together a small event they initially thought would take place in the back room of a library. By the time it ran, Ms. Peck had gathered over 100 attendees, hosted at a formal venue.
While it was satisfying to see the event happen, “I noticed the room was not as diverse as it could be,” Ms. Peck recalls. She decided to launch Toronto Womxn in Data Science, making it intersectional to attract and promote BIPOC women in the field.
The spring conference has run annually ever since, featuring sessions on topics such as responsible AI, data feminism, health equity and confidence and self-advocacy. The group now runs a podcast aimed at young women called Data Drop, and Ms. Peck is developing a fellowship that will support an emerging professional in developing a data product.
All these initiatives are aimed at bringing more equality to the white-male-dominated field of data science, Ms. Peck says. The goal is to help women – especially women of colour – network, learn, find mentors and, most importantly, see that they belong in this growing and well-paid industry.
Ms. Peck says she’s heard from women who have joined the profession because her organization showed them it was possible.
“They didn’t think they were a fit for data science,” she says. “After one of our events, they felt confident enough.”
Data science on the rise
Canada’s digital economy is hot, surging despite the economic impacts of the pandemic.
In August, the Information and Communications Technology Council (ICTC) reported that jobs in Canada’s tech sector and technology roles in all other sectors jumped to more than 11 per cent of the country’s total employment from 9.5 per cent before the pandemic. ICTC forecast that 2.26 million people will work in digitally skilled positions by 2025 – an increase of 250,000 positions.
If the future is digital, a big slice of that future relates to data science. Back in 2014, Harvard Business Review dubbed data scientist “the sexiest job of the 21st century.” In 2021, Glassdoor ranked it number two for best jobs, with a median base salary of US$113,736.
Virtually every industry need professionals to collect and contextualize data to help with decisions regarding new product development and other key business choices, Ms. Peck says. “Anywhere information needs to be transformed into insights, data scientists are working there.”
Across all industries that use data scientists, there’s a shortage of professionals. In a 2020 report, global management consulting firm BCG reported that women make up just 15-22 per cent of the work force in data science. Increasingly, companies are establishing leadership positions such as chief data officer, but most of those positions are held by men, Ms. Peck adds.
The lack of women in data science is a problem that goes beyond opportunity. The Center for Global Development, a non-profit think tank in Washington, D.C., noted in a March 2021 blog post that the underrepresentation of women in data science increases the risk that data-driven policies will be designed and implemented using biased data. “Once data sets become biased, they are difficult to fix,” the post notes.
Roadblocks to advancement
The barriers to women entering STEM jobs begin at an early age, Ms. Peck says. She remembers earning Bs and Cs in math and being told to not bother taking it in Grade 12. As a student at York University, Peck transferred into economics, teaching herself calculus on her own time.
Data science, as a new field, has a myriad of ways in, including college programs, boot camps, university undergraduate and graduate degrees and continuing education certificates. (For her part, Ms. Peck graduated from the Analytics for Business Decision Making Program at George Brown College in 2016, having already completed an economics degree at York.)
Ms. Peck says many mid-career women already use data in their jobs and may have the skills to pivot, but don’t realize it.
Once in a data science job, women can struggle to get support from colleagues to do their jobs effectively, Ms. Peck says.
“You can have trouble getting what you need to get your work done – I’ve had experience with this and I’ve heard other women have too,” she says. “It’s a lot of politics and there are not enough allies that make it welcoming enough for women in data to stay.”
While all women can experience these challenges, Ms. Peck notes that BIPOC women can experience outright discrimination, microaggressions, pay gaps and being excluded from work or promotions. In a 2020 report, U.S. data and analytics recruiters Harnham found that Black people accounted for just 3 per cent of the data and analytics community.
As companies grapple with a shortage of professionals, Ms. Peck hopes more businesses will create workplace cultures that attract and retain women so they can fill positions. In devoting herself full-time to Toronto Womxn in Data Science, she hopes to move faster to nudge her industry forward.
“I feel there’s a time clock on me,” she says. “We need women in data science so that innovation can be more inclusive to the people it’s actually for.”