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Want a data science job in banking? Here's why you probably won't succeed.

Why most data scientists are no good for banking

Just because you're a data scientist, don't presume you'll get hired by an investment bank.

This is the message from Shary Mudassir, a managing director in global equities trading at RBC Capital Markets. “It’s hard to attract and retain highly capable AI talent – if you get 100 applicants, then 90 of them are not really data scientists, and if you get 10 average data scientists, they won’t be as effective as one really good data scientist,” Mudassir says. “The 99th-percentile [employee] will add 80% of the value for the entire team.”

He should know. Mudassir is tasked with building out an artificial intelligence lab for RBC Capital Markets in Toronto, opening in May. It will be in addition to the Borealis AI lab, which the bank's opening in Montreal to join existing Borealis labs in Toronto and Edmonton.

RBC is betting that the data science, artificial intelligence and machine learning laboratory will give it a leg up in trading – and in attracting the best STEM talent. “The Global Markets AI Lab is a special space we’re setting up on the trading floor in Toronto, with more than 400 traders across asset classes, including FX and commodities," says Mudassir.

“We’re the first bank in Canada to create an AI lab on a trading desk, with scientists and engineers solving trading problems using AI in their toolkit,” he claims.

The plan is to bring in experience algorithmic traders, as well as business and domain knowledge experts, to present how they do business and trade and think of new ways of solving their existing problems with AI and machine learning. RBC will then turn them into commercialized products.

RBC executives believe that having an AI lab integrated with its trading unit will help the bank to attract the best talent. This is where the challenge begins.  “I’m always about organic growth, hiring the right people rather than hiring quickly,” Mudassir says. “With this lab in place, we’ll likely have to find senior resources to manage people in the lab, and as my mandate gets bigger, I will need help to run this lab as well."

Many data scientists and artificial intelligence professionals have cut their teeth in a research environment, but Mudassir suggests this isn't the kind of experience he's looking for.  “We’re not an R&D shop – everything we do becomes part of a large operational system,” he tells us. “You have to live and die by your work, but this is getting applied to trading strategies, applying cutting-edge AI innovations to real-world problems specifically on the trading side.

“The juniors we hire are very much driven by seeing their work play out in the real world, not just to do research, but also to enhance the field of AI,” he says.

Photo credit: StockFinland/GettyImages

AUTHORDan Butcher US Editor
  • Bo
    28 March 2018

    Says the banker who's only alpha is front running client flow.

    Machine learning and artificial intelligence are marketing buzzwords. The statistical methods have been used heavily since the 90's. You can fool upper management with buzzwords.. until they catch on several years later.

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