Jonathan Woods

May 25, 2021

There’s a skill that teams at Scotiabank prize when recruiting top new graduates for AI-related co-ops and jobs. It’s one required to thrive in a bank that calls on its employees to learn multiple AI techniques, tackle a diverse set of AI use cases, and walk the full path from data set to deployment.

In a word, that skill is finesse – a blend of competence, versatility, and communication skills – and it comes at such a premium that it even trumps research credentials. “We don’t look at academic publications that often,” says Dr. Yannick Lallement, Scotiabank’s Director of Data Science & Machine Learning. “They’re important, but not a requirement. What is a requirement is that people can think on their feet, understand their internal clients’ use cases and real world situations, and describe how that gets reflected in the data.” In other words, he says, “the best candidate is someone who knows how to think.”

This priority stems from the demanding and dynamic nature of AI work at Scotiabank. AI engineers and data scientists, including recent grads, are called on to work on many different kinds of machine learning projects at the bank – from using NLP for sentiment analysis to refining personalized marketing to building a cash flow prediction tool. Each project impacts a part of the business and involves working with different internal clients. In every case, AI engineers and scientists need to build productive relationships with those clients, understand their desires, and frame them as machine learning use cases, and then explain why their proposed data and machine learning approaches are the right ones.

This takes a deft touch; scouting for co-op students and new grads with technical acumen, communication skills, and an ability to think through a use case from first principles can be a tall order. One place Scotiabank uncovers such candidates is the Vector Institute. Through its sponsorship of Vector, Scotiabank can access AI-focused recruitment events and the Digital Talent Hub – an online platform designed to connect employers with vetted machine learning talent, including many from Vector-recognized AI master’s programs.

Lallement has attended Vector events and says, “They have a high calibre of students. It’s probably the highest I’ve seen in the different types of fields we look for.” These have been fruitful channels, as Scotiabank has hired several students that have come through Vector or been connected to it.

Enter Ivy Wu. Wu emigrated to Nova Scotia from Guangzhou in 2015 before making her way to Ontario to do a Master of Data Analytics with a specialization in AI at Western University, a program officially recognized by Vector for producing graduates with AI skills sought by industry. She applied for a co-op role on Scotiabank’s data engineering team using Vector’s Digital Talent Hub, and then attended Research and Careers in AI: Financial Services Edition, one of Vector’s sector-specific career events, where she met and spoke with recruiters from the bank. After being invited to an interview, facilitated by Vector’s Talent team, she was chosen for the role and immediately went to work building and deploying data pipelines and implementing new frameworks for data lineage.

Wu and Scotiabank turned out to be a great fit: upon completion of the co-op in late 2020, she accepted a full-time role at the bank. Working at Scotiabank, Wu says, “I built up skillsets for developing reliable frameworks or mechanisms for data collection, learned multiple data engineering tools, and applied them in my work. But the most interesting thing for me during the co-op term was that I met a great team and great leaders.”

This illuminates another element of Scotiabank’s approach: the flip side to finding promising machine learning talent is highlighting Scotiabank as an attractive workplace. A key attraction the bank provides is the broad variety of machine learning challenges that AI engineers and data scientists get to tackle, and the new learning involved with doing so. “We have many different use cases to work on. If you work with us, you’re not going to spend your time on only one use case. You’re going to spend it on many,” says Lallement.

Another attraction for talent is culture. “The bank places a lot of emphasis on building a good environment where people actually congregate, enjoy working together, and want to achieve a common goal,” Lallement says. “That comes from the top.” This is reflected in the fact that Scotiabank is perennially listed as a top place to work in Canada, and puts major resources behind programs like ScotiaRISE – the bank’s 10-year, $500 million initiative to promote economic resilience among disadvantaged groups.

Scotiabank’s partnership with the Vector Institute has allowed the bank to find the special AI talent they seek and support the development of more. “Having Vector based here in Toronto positions us as a leader,” Lallement says.

“And of course, being a leader attracts talent.”