Hedge funds and asset managers are scrambling to poach talent from Silicon Valley and attract computer scientists fresh from college to capitalise on the investment industry’s hottest frontier.
So-called quantitative financiers, or quants, have for years come up with innovative, complex ways to analyse and trade on company earnings or economic releases. But thanks to huge gains in computing power and algorithmic research, they are now pushing into “unstructured data” such as internet searches, social media, satellite images, earnings calls or weather patterns to find market signals and overlooked trading opportunities.
To do so they need to deploy innovative, increasingly powerful quasi-artificial intelligence algorithms, ratcheting up demand for computer scientists to do coding that is beyond mathematicians and physicists.
“Traders used to be first-class citizens of the financial world, but that’s not true any more. Technologists are the priority now,” says Jared Butler, a headhunter at Selby Jennings. “It’s easier to hire a computer scientist and teach them the financial world than the other way around.”
Two Sigma, a $28bn hedge fund, and BlackRock, the world's biggest asset manager, earlier this year snapped up two former Google engineers, underscoring the mounting demand for computer scientists to help gain a digital edge in the cut-throat money management industry.
Two Sigma is one of the hedge fund industry’s fastest-growing companies, and is led by computer scientist David Spiegel and mathematician John Overdeck. They recently hired Alfred Spector, formerly vice-president of research and special initiatives at Google, as chief scientist.
BlackRock hired Bill MacCartney, a former Google engineer, this year as a managing director in its "scientific-active equity" team, where he will bolster the asset manager's efforts to mine data sets for lucrative investment opportunities. In late 2012, David Ferrucci, head of IBM's Watson supercomputer, joined Bridgewater Associates to build the $168bn hedge fund's artificial intelligence arm.
“Quants have always been in demand, but the structure of the demand has changed over the past two years,” said Michael Karp, chief executive of Options Group, a recruiter. “The world is becoming more technologically demanding, and a lot of firms now need computer scientists that can code algorithms.”
The problem confronting quant money managers — and banks rushing to revamp and build their technological capabilities — is that the financial industry is less attractive than Silicon Valley’s biggest companies or hottest upstarts, especially in recent years.
Dennis Ruhl, head of JPMorgan Asset Management’s quantitative behavioural finance unit, said: “We absolutely need more computer scientists, but it’s a challenge as the financial industry has suffered an image crisis in recent years.”
Many asset managers are, as a result, establishing closer ties with universities so they can tap directly into the pipeline of talent, or setting up contests such as the Man AHL Coder Prize or the WorldQuant Challenge to unearth self-taught programming talent.
Mr Butler at Selby Jennings concedes that attracting top tech talent is a big obstacle for the finance industry, but said the potential salary and intellectual challenges of a career at the more innovative trading firms or hedge funds is still an attraction to many computer scientists.
"It's a constant thorn in my side. Whenever I find a red hot programmer they'll have a job offer from Google, Uber or somewhere else. But there is an allure in building a successful trading strategy as well."
Copyright The Financial Times 2015
