With great data comes great responsibility. That was one of the messages imparted at a recent Linkedin Live panel on working in the machine learning field, featuring insight from several machine learning researchers at RBC Borealis.

Hosted by Jaime Trivino, senior talent acquisition lead at RBC Borealis, the panel included Greg Mori, senior research director; Leila Pishdad, senior machine learning researcher; and Eric He, machine learning research lead.

Remarking on what makes working at RBC Borealis an enriching career choice, Mori said that research teams have an opportunity to build products that make a true impact on people’s lives. “And at the same time, you have access to data that covers a huge segment of the Canadian economy, such as capital markets. And along with this comes a ton of responsibility because we’re part of such a large bank, because we can have such an impact on people’s lives, we have to make sure that the technologies we build are done so responsibly.”

Responsible AI has been a key obligation for anyone working in the field, and the latest research on responsible AI points to how this sector is maturing quickly.

Mori also outlined the company’s main buckets of research: product development, incubator, and north star research. He noted how the research team participates in all of areas, and in product development the team leverages techniques honed in other sectors and “really uses them to build products in conjunction with our product manager and engineering colleagues in the incubator programs. What we do is we do small proof of concepts that help us explore what could be done.”

At north star research, investing in the company’s long-term future is paramount, Mori added. “We build algorithms that will help support our product development and incubator work into the future.”

Concerted consideration of quality is top-of-mind at RBC Borealis, Pishdad shared. “The applied research that we do has is actually more challenging than the type of applied research that you could see in other organizations. So we’re really looking for machine learning challenges. And we have to be very careful, very diligent about our work and make sure that everything is at the utmost quality,” she said.

Choosing RBC Borealis as her next career venture was a no-brainer for Pishdad for two key reasons. “The fact that I can do both fundamental and applied work was very special to me because this is not something that you will get in many organizations,” she said. “Also, at RBC Borealis, we can see different groups of women and ethnicities at very high leadership roles. Many companies talk about diversity and inclusion, but seeing it actually happen is something different.”

For He, gaining experience in coding caused a ripple effect that levelled up his skills in other areas. “I had to learn to write industry-level code at RBC Borealis, which is actually pretty challenging for a fresh PhD graduate…and now I’m much more efficient and effective at conducting research.”

For anyone seeking a role at becoming a machine learning researcher, He says the right person will relish the challenge. “If you’re interested in learning from engineers and product managers and if you want to roll up your sleeves and make things happen, RBC Borealis is the place for you.”

Want to build game-changing statistical models? Are you interested in a career in machine learning research? Find out more about our research team and explore current opportunities here. You can also find out what a day in the life looks like for a Machine Learning Researcher at RBC Borealis by checking out this recording of the LinkedIn Live event.