How These Three Women Made Mid-Career Pivots Into Data Science

In the U.S., women earn about 40% of undergraduate degrees in STEM fields overall, according to a recent study, yet receive less than 20% each of the degrees awarded in computer science, engineering, and physics. That leaves a pretty serious gender gap in one of the most in-demand fields around: data science.

But while widening the so-called “talent pipeline” is one important way to narrow that gap, it’s not the only solution. If girls can be exposed to STEM programs early on in their educational careers, there’s no reason why adult women can’t make the leap into a data-based role later on in their professional ones. In fact, that’s exactly what these three women did—and not from adjacent roles that were heavy on computational skills, but by pivoting out of creative jobs. Here’s how.

Making Numbers Tell A Story

Rebekah Iliff, who’s 38, spent the first half of her career exploring her knack for the humanities. She graduated from college with an undergraduate degree in philosophy and went on to acquire a double master’s degree in organizational management and applied community psychology. For the first half of her career, she worked in PR, including running her own agency for tech clients.

In her PR work, Iliff says saw herself as a storyteller—being able to think creatively by putting disparate pieces together. A in her world could just as well be connected to D as to B. The only hitch, she felt, was that results of those connections were more a matter of faith than calculable ROI; it was more art than science.

Frustrated by the lack of accountability that created, Iliff was introduced to the founder of AirPR, a company that had just launched in order to solve that problem. Having launched nearly 100 startups in the U.S. market, Iliff knew the high value that founders placed on getting predicable outcomes from their PR investments, which were too often elusive—leaving Iliff and her business partner to have to constantly justify their budgets on what scant data they actually had.

Iliff signed on in 2012 as AirPR’s chief strategy officer and “went from one side of the equation to the other almost overnight,” she recalls—”from writing and creating stories to taking all the information PR generates and putting a value around it using technology, machine learning, artificial intelligence, and big data.”

Initially the company’s only female employee (it’s now about 22% women), Iliff reflects that growing up with three brothers helped make her entry into a male-dominated field a little bit easier. “Working with engineers has forced me to learn a completely new language of communication,” she says. “Engineers think linearly.”

But Iliff found that storytelling skills she’d spent the first part of her career developing still came in handy, too. “You have to learn to ask the right questions and make things more concrete. You need the patience to understand where someone is coming from.”

Using Data To Design A Career—And Beat Gender Bias

Like Iliff, Sce Pike never imagined working in data. In college, she’d dreamed of being an artist or singer, majoring in fine arts and anthropology. Her career path from that point forward was anything but direct. Pike, now 41, segued from art to web design to “human factors design,” which studies human-machine interactions, for the telecommunications giant Qualcomm.

Then in 2010, Pike left to start her own agency in Portland, Oregon, called Citizen, which initially focused on improving the user experience for smartphone companies. Having mastered the career pivot, Pike ultimately decided to shift Citizen’s focus toward the quantified-self movement, or as she calls it, the “Internet of You”—basically, the tech ecosystem that allows individuals to track their own biometric data.

Pike started right in her own backyard. First, she had some of her own employees voluntarily track their own sleeping, eating, and workout patterns. The idea, initially, was to create a healthier company, an experiment that caught Wired‘s notice in 2013. The article led to new clients and soon enough let Pike push the company headfirst into data—from connected health to cars and finance—using analytics technology to solve a wide array of self-management challenges.

She didn’t stop there. In addition to Citizen, Pike spun out a separate company, IOTAS, to provide smart-home services to renters, not just homeowners.

“Looking back, I’m amazed where I am now,” Pike says, noting that she’s had to modify her professional style and attitude in order to succeed. “Men can tout their personal brand. If women do it, it comes off as bragging. If a male counterpart does it, he’s so cool.” That’s where Pike says data came in handy.

“I have had to approach my work with logic, research, and great design,” she says, “rather than to tell you it’s cool.” Indeed, Pike’s experience is born out by the research. Studies have indicated that women who promote themselves in the workplace face disproportionate risks of doing so relative to men, who are more often rewarded for touting their skills and experience.

In other words, Pike pulled off her numerous self-transformations thanks in no small part to her quantitative chops. Each time she found her career or business heading in an unexpected direction, she calculated her next move and made sure the numbers backed it up.

From Software Marketer To The Fed’s First Data Chief

Micheline Casey had a more straightforward trajectory, starting in marketing for software companies before getting an MBA in information systems. “I fell in love with technology from my very first job,” she says. “I really like the possibilities of tech to enable and expand business, society, people.”

Casey did some consulting work for small companies, along with a brief stint at IBM Global Services and a stab at creating her own internet startup, which became a casualty of the 2000–2002 stock market crash, along with so many other dotcom businesses. But the bursting of that bubble prodded Casey toward a data role. She took a job in customer sales and product development with a company then called ChoicePoint (now LexisNexis Risk Solutions), which had been spun off from Equifax.

“We were at the forefront of the data industry” at the time, Casey says. “I fell in love with data. It’s rich enough to drive business decisions and innovation in ways that technology alone can’t deliver.” After five years at ChoicePoint where she served as identity management director, Casey was appointed Colorado’s first chief data officer, tasked with improving the use of data and technology in the state, a position she held for four years.

At the end of her tenure, Casey moved east to start a consulting practice on data strategy, helping companies leverage data for their business. Before long, she was recruited by the Federal Reserve Board to serve as its first chief data officer. Casey says she enjoyed her work there but found the Fed’s environment challenging. In fact, she says she had three strikes against her there: First, she wasn’t an economist, which made her a second-class citizen at the Fed. Second, as a woman she was a minority in a male-dominant world.

And third, Casey was trying to innovate in a risk-adverse culture. “I’m not a wallflower,” she says (pointing, like Iliff, to her upbringing as a source of her resilience: Casey grew up with no fewer than seven brothers). “I’m willing to challenge the status quo.” Since leaving the Fed in 2015, Casey has consulted to help organizations do more with their data, served on the board of an energy organization, and mentored girls in a STEM program.

To be sure, these women are exceptional talents—including statistically. But each of their career paths shows that the path into highly successful data jobs doesn’t just come through the university system’s talent pipeline alone.