Tomorrow’s bankers and dealmakers need data science basics to break into the field.In response, leading business schools are rolling out dozens of data science and tech classes.Insider spoke to leaders at Wharton, Columbia, and Northwestern about the transformation.Training to become an investment banker used to be about studying subjects like accounting and financial modeling after getting accepted to a top-rated business school.
These days, things are changing.Aspiring bankers are starting to realize they stand a better chance of scoring a hot Wall Street job if they also come equipped with skills once reserved for back-office staff, like coding, data science, and software engineering.
It’s a reflection of a changing Wall Street — and it’s forcing the nation’s top business schools to work at breakneck speed to keep up.
For the current 2022 spring semester, Columbia Business School has 30 class sections tied to analytics and digital learning with 1,810 enrollments, up from 20 sections with 1,321 enrollments in the spring semester of 2021.
Wharton, the nation’s second-best graduate business school according to US News & World Report, has added at least 18 new such classes between its undergraduate and graduate programs in recent years, including a new “Data Science for Finance” seminar that it launched in 2020.Meanwhile, Northwestern’s Kellogg School of Management, ranked fourth for 2022, has launched a 15-month MBA track merging business skills with computing know-how in tandem with the University’s engineering school.
Daniel Guetta, a member of faculty at Columbia Business School, told Insider that demand for his Business Analytics 2 seminar has been relentless since the school, ranked seventh on the US News & World Report list, launched the course three years ago.
“We started with one section and then that was full,” Guetta, director of Columbia Business School’s Center for Pricing and Revenue Management and Business Analytics Initiative, said in an interview with Insider.
“So we added a second section, and a third section, and a fourth section.
We’re up to seven or eight at this point, and they still are all full.And there’s still not enough seats for all of the students who want to take this class.And we just keep on adding sections.”
Columbia Business School is in the process of onboarding additional faculty to teach some of these seminars, Guetta added, “because there’s only so many hours I have in a year.”
W all Street sees these skills as ‘necessary’ to do the job To be sure, interest in how to merge computing with business isn’t limited to aspiring financiers.People armed with MBAs pursue many different career paths from consulting and business management.And technology now touches nearly every aspect of the US economy.
But experts say much of the demand is being fueled by students seeking to work as dealmakers at investment banks and private-equity firms, or traders at hedge funds.Aspiring financiers comprise large constituencies at business schools, sometimes exceeding one-third of the student body at many top MBA programs.
In 2021, 36% of the student body at Columbia Business School went to work for financial-services firms, the school said in its annual employment report .Wharton’s 2021 employment report uncovered similar findings, with just over 35% of the 2021 class accepting full-time offers from financial-services companies.
Financial firms, for their part, are increasingly relying on so-called big data to help them better advise their corporate clients or their portfolio companies — or to identify new investment opportunities.As the skills needed to do these front-office jobs become increasingly driven by data, students and employers are recognizing the trend lines.
“It is clear to the banks that these skill sets are beginning to be necessary for you to be able to do your job,” Costis Maglaras, dean of the business school at Columbia University, told Insider.
They “know that they need skills in data science, and partially the reason they know this is because, when they interview for jobs, I’m being told over and over again, they’re being interviewed about what they know,” explained Eric Bradlow, vice dean for analytics at Wharton.
In some cases, Bradlow said, financial and consulting firms are telling interviewees: “Here’s a data set — analyze it and answer the following question to us.”
That doesn’t mean that investment bankers, dealmakers, and other front-office finance industry workers are in danger of losing out on the jet-setting and hobnobbing privileges of their jobs.
“It’s not about replacing human judgment” through these tools, said Bradlow.”It’s about supplementing it.”
“Information is important to our clients,” explained Patrick Kandawire, deputy chief operating officer for capital markets at Morgan Stanley.”The more tools you have in your toolkit, the better equipped you are to really understand your client needs, where the market is going, what the latest and greatest insights are within the context of how you’re trying to prosecute the business.”
The chance to think like a hedge fund PM Dan McKeon, a 21-year-old undergraduate, took Wharton’s new “Data Science for Finance” last semester because he doesn’t want to be left behind.
“You kind of have to get with the times,” he said of data science’s growing importance, “or else you’re going to fall behind.”
“The world is moving quickly towards a point where data is going to be involved in pretty much every decision we make,” said McKeon, who intends to work in the financial-services field after graduation and interned for Miami-based hedge fund Buckley Capital Partners last summer.”Not knowing where the data comes from or how the analysis is performed is going to leave people uncertain or confused.”
As part of his final project, McKeon worked with a team of students to analyze hundreds of thousands of data points pertaining to credit-card transactions to find a relationship between the data and publicly-traded equities returns in the same way that a savvy hedge fund portfolio manager might.
You kind of have to get with the times or else you’re going to fall behind.Dan McKeon, Wharton student.