- There is growing demand for data-science talent across industries, and while Wall Street and other finance companies might be improving its reputation in these circles, it hasn't gotten any easier to find the right people.
- Hedge funds are feeling pressure from Silicon Valley darlings, which are growing their presence on the East Coast, as well as other industries who are beginning to realize the value of crunching their own data.
- At some funds, like Point72, data scientists are so in-demand that some even have longer non-compete periods than the portfolio managers making the investments.
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"Data is just a huge piece of what everyone is doing now."
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Uber and Lyft have struggled since going public, while Facebook has become a favorite punching bag for politicians thanks to its privacy scandals, but even those dings against Big Tech haven't helped finance's pitch much when trying to lure data-crunchers.
Data scientists and others that can harness and monetize the exploding number of data streams pouring into the investment management industry have been in high demand, from quant funds and fundamental stock-pickers alike.
The challenge for recruiting this type of talent historically has been the competition from Silicon Valley startups that can offer a more familiar consumer brand name as well as the lure of upside in the form of equity in a pre-IPO company.
Recruiters and hedge funds told Business Insider that this challenge still exists, despite Silicon Valley's high-profile setbacks, and new obstacles have emerged on top of that.
We aren't competing with just tech for this talent, said Hinesh Kalian, director of data science for Man Group. Other industries like logistics, retail, and advertising are beginning to crunch data as well.
"My expectation is that the role of data scientists has become commonplace across all industries," he said.
For some big hedge funds, data scientists have become just as valuable as the money managers; occasionally at Steve Cohen's Point72, for example, data scientists will have longer non-compete clauses than the portfolio manager they are working with, sources tell Business Insider. Point72 declined to comment.
Big tech companies' expansions on the East Coast, like Google's New York campus and Amazon's investment in northern Virginia, has also added to the difficulty of recruiting data scientists, said Ryan Tolkin, the chief investment officer of Schonfeld Strategic Advisors.
Previously, he said, finance was able to recruit students from top schools on the East Coast who didn't want to move out west.
"I think if anything is becoming more and more competitive," Tolkin said.
Finance has improved its standing in the data science world, several industry observers say. But hedge funds' performance lately doesn't exactly help them sell themselves.
Jason Schulman, a managing director for recruiting firm Long Ridge Partners, said people in tech "may be more receptive to moving over to finance now," but last year was not only tough for Silicon Valley — several of the most popular hedge funds for data crunchers had tough years.
AQR and WorldQuant both started 2020 with layoffs, and Bridgewater lost money for the year. And while fundamental managers are coming around to the idea of bringing on data scientists, the "merging" has been hard, Schulman said. Balyasny last year cut a team that mixed quant and fundamental strategies, known as Synthesis, and was running a $2 billion book.
"Some of the funds are still trying to figure out how to intersect" the two disciplines, Schulman said.
For hedge funds to continue to compete for top tech talent, Tolkin believes the lines between hedge funds and private equity will have to continue to blur so capital is more permanent. A couple quarters of high costs due to a big tech build-out or a recruiting efforts can't scare off investors, he said. There are projects that his firm has undergone that haven't shown returns for more than a year, but were necessary.
"You also need to have scale, because the industry has gotten so expensive," he said.
At Man Group, the relationship the firm has with Oxford University has helped introduce some young talent to the firm early on, Kalian said. The ideal candidate for the firm, though, is not someone fresh out of undergrad — Man is looking for someone who is two years out of university, Kalian said, and has a master's or PhD in a field like statistics or machine-learning.
Kalian said Man Group's data scientists need to be able to communicate what they are finding in the data to a degree that isn't required in other industries, because they are often searching for the answer to a question within the data itself.
"It's not as narrow of a role as it might be in the tech world," he said.
Recruiting "hasn't gotten any easier," and isn't expected to, according to Schulman.
"Data is just a huge piece of what everyone is doing now."
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