Vector’s Shingai Manjengwa named one of Ryerson DMZ’s Women of the Year
March 23, 2022
March 23, 2022
By Ian Gormely
March 23, 2022
Shingai Manjengwa, Vector’s director of professional development, has been named one of Ryerson DMZ’s inaugural Women of the Year, a list of 46 women chosen for their “outstanding accomplishments and contributions to creating impact.”
“This recognition is for all the women in tech building things, finding solutions, and chipping away at challenges,” says Manjengwa on the award. “Increasing participation of women expands our solution space and enhances our problem-solving capacity.”
Chosen from more than 600 nominees, the award was “curated by the tech community to honour inspirational women within the Canadian tech ecosystem.” Janet Bannister, Managing Partner at Real Ventures and a Vector board member was also included on the list, which includes women from “diverse backgrounds and industries including startup founders, corporate leaders, non-profit trailblazers, and emerging youth.”
Manjegwa credits a skill she developed as a translator as a key reason for the success she’s experienced. “I’m able to deconstruct complex topics and problems into concepts that different people can understand,” she says. It was a capability she developed out of necessity.
Manjengwa received a Bachelor of Commerce degree from the University of Cape Town, with majors in Politics, Philosophy, and Economics. But after graduation, she found work as a data analyst, a field unrelated to her degree. “I had to figure it out,” she recalls. “That involved speaking with developers — the people working with the hardware, software, or algorithms — then linking what they told me to the industry side of the business and translating all that into adoption. “Once I started asking questions, people were forthcoming. But I had to go to them.”
After moving to Toronto and earning a Master’s degree in business analytics from NYU Stern, Manjengwa founded Fireside Analytics in 2015. “The company was supposed to be just consulting,” she says. “If you have a dataset, I’ll look at it, and write a report.” She quickly realized that there was as much of an appetite to understand how she came to her conclusions, as there was for the conclusions themselves.
A chance meeting with folks from IBM led to her contributing education materials to the tech giant’s Cognitive Class platform. “My approach to teaching really reflected my own journey learning the industry,” she says, deconstructing every aspect of the practice down to their fundamental concepts while asking lots of questions and making zero assumptions. “I infused that into the case studies and courses I made and it resonated with many people.” Her work as an educator has opened doors for others that were once closed to her when she first stepped foot in the data science world. To date, her courses have had more than half a million registered users.
Although the technology keeps changing — whether you call it machine and deep learning or data science — Manjengwa’s work at Vector doesn’t stray far from where she started: taking great AI research and translating it into concepts and products industry can absorb, be it talks, blogs, workshops or courses.
“After all these years I’m still a translator.”