However attractive it may be as a place to work, financial services tend to be seen as pretty dry. The datasets may be large and recursive, the problems may be complex and the outcomes immediate, but the industry is inherently about money and making more of it.
This might be why a growing number of major quant employers are offering something extra to their employees: the opportunity to work on problems outside financial services.
Take, for example, the newly launched ADIA Lab, which is supported by the Abu Dhabi Investment Authority (ADIA), and which counts Marcos Lopez de Prado, head of quantitative R&D at ADIA and Alex Lipton, head of quantitative research and development at ADIA , among the people on its advisory board. Both Lipton and Lopez de Prado are longstanding finance buy-side quants. At ADIA lab, both will get the opportunity to explore data related to “broad research goals that are not specific to investment-related applications.” In an indication of what these explorations will involve, other members of the advisory board are drawn from biomedicine, material sciences and epidemiology.
ADIA quants aren’t the only ones extending their remit. Steve Cohen’s hedge fund Point72 is allowing its quants to cross over into the work being done at the New York Mets (which Cohen also owns), with a focus on improving data analysis and technology.
And one of the earliest escapees from quant finance was David Elliot Shaw, founder of hedge fund DE Shaw. He set up DE Shaw Research in the early 2000s. The company, which employs various research scientists, is using machine learning to build super computers to look at molecular dynamics.
It’s also becoming increasingly common for quants in finance to maintain relationships with academia. Naftali Cohen, a data scientist at hedge fund Schonfeld, acts as a lecturer for industrial engineering and operations research at Columbia University, for example.
One finance quant tells us it helps a lot to have a side hustle. When finance quants work part time for universities, for example, the universities receive lecturers who can teach students about “actual use cases, actual tools, and real data sets.” Meanwhile, the quants benefit from the opportunity to identify the most able student hires before anyone else.
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