Connor Donovan’s (MMA ’21) career in the energy sector has taken him on an international journey.
Connor Donovan (MMA ’21)
As an energy analyst in Denver, Colorado, he works on building forecasts for power markets across the U.S. at Ascend Analytics. Before that, Donovan worked at the International Energy Agency in France, where his team developed projections on how the world’s energy economy would change in 20 to 30 years. He says the Rotman Master of Management Analytics program elevated his skills and confidence in between those roles, giving him a launchpad into the business communities in Canada and the U.S. that was hard to find elsewhere.
“In the energy sector, there’s so much data from all different sources, and you need to know how to wrangle it, clean it up and present it in a clear way,” says Donovan, who has a civil engineering degree from Queen’s University and a Master of International Energy from Sciences Po in France.
After several years of work experience in his field, Donovan decided to return home to Toronto to bolster his analytical skills for future roles.
“Forecasting in the energy sector is fickle and it can change very quickly. It’s critical to understand where the fault lines are in the data, and that was something the program offered — and delivered,” he says.
“You learn to be a translator for people — distilling problems into a clear message, instead of analyzing data just for the sake of analyzing.”
—Connor Donovan, Master of Management Analytics '21
Turning complex data into business solutions
For Donovan, the most valuable takeaway from the program was knowing how to effectively solve business problems from a data-driven perspective.
“You learn to be a translator for people — distilling problems into a clear message, instead of analyzing data just for the sake of analyzing,” he says, noting that Prof. Ryan Webb’s course on predictive analysis and Prof. Gerhard Trippen’s course on big data analysis were especially eye-opening.
“I found the professors were very in touch with what's going on right now in the business community — where industries are going, and what kind of questions need answers,” he adds.
“The program is great for people who know how to think in numbers, but also want to learn to present and talk in numbers.”
‘The next Tesla’
For Donovan’s team practicum project, the group was paired with CIBC, who gave them an interesting goal: “We want to identify the next Tesla.”
“That could mean a lot of things, and they wanted to see what we could come up with,” says Donovan.
“We felt the most important thing was really understanding what they are after, how we can translate it into something that would be useful for them and build on.”
After conversations with the CIBC team, Donovan’s group concluded that they wanted to get a pulse on new opportunities in different sectors that might emerge from textual data — information that might not appear in financial market data.
The team created a natural language processing tool that takes text data from sources — like Reddit, Twitter, The New York Times and academic articles — and identifies new technologies coming into conversation. The tool sifts through the data and presents only what is relevant to a specified sector.
“Having completed my MMA, now I can go into the business community and level with them in their language. I can show them how all this information that’s out there now — that maybe wasn’t there 10 years ago — might be useful to them,” says Donovan.
Written by Jessie Park | More Student Stories »