Michael Purves - Do You Need to Study CS to Succeed on Wall Street?

As technology develops rapidly, and computer science becomes an increasingly popular major, Wall Street is hiring more quantitative analysts than ever before. Computer Science students no longer look only towards Silicon Valley: instead, they have been receiving very attractive offers from financial institutions in New York, London, and Singapore. The influx of “quants” on Wall Street has put fear in the hearts of Economics majors. Will traditional floor traders be replaced by tech geniuses and mathematicians? Or, even worse, by computers and robots?

Michael Purves, the Chief Global Strategist and Head of Equity Derivatives Strategy at Weeden & Co., would argue that there will always be a place for people trained in economics, policy, and business. He says, “On Wall Street, there’s a vast wilderness of data and things to think about, and people have to contextualize that. So there’s a huge role for people that are not on the quant path.”

In fact, Purves himself did not receive a traditional “Wall Street education.” Not only did he not major in computer science or math, but he didn’t study economics or finance either. Purves was an architecture major. “I would not change my degree in architecture for anything,” Purves says. He argues that his architectural training taught him valuable skills that he uses today, including looking at problems from different angles. When designing a building, an architect produces three sketches: the floor plan, the elevation, and the cross-section. This allows contractors to see the plan from different angles; a building can not be constructed without all three types of plans. Purves compares these multiple plans to his approach to finance. He needs a variety of different viewpoints, both from the tech and math side and from the communications side, in order to do his job.

The collaboration between quantitative analysts and executives who are not mathematically trained is important, but difficult. Purves describes “quants” as speaking a different language. When explaining their latest algorithm, “it’s as if they are selling coffee in Turkish, but pitching to an audience that only speaks English.” The divide between the math/tech language and the language of more classically trained finance workers can be bridged if people studying humanities take the time to learn basic math vocabulary, and vice versa. In his advice for students, Purves says, “don’t be afraid of quant: do engage with it as much as you practically can. Learn a few words of Turkish, and everyone will get along.”