Financial services firms, including hedge funds, proprietary trading shops and even mutual funds, are falling all over themselves to hire talented artificial intelligence (AI) and machine learning experts, data scientists, programmers/developers/coders and quantitative traders. There is plenty of competition for such talent. Top candidates are in control.
Adam Zoia, the founder and CEO of Glocap, a recruitment firm, said that the big new trends he’s seen are artificial intelligence and data science coming into serious demand on Wall Street.
“AI and data science are being used more across the financial services industry in the context of making better business decisions and which stocks to go long on or short,” Zoia said.
For many of the positions firms are looking to fill, data analysis is a better description than quant. At the non-quantitative fundamental hedge funds, data analytics specialists are informing investment decisions for the traditional portfolio managers.
“There’s a lot of hiring going on there,” Zoia said.
“We see a big uptake in interest in data science and the machine learning space,” agrees Victor Tang, a senior associate of quantitative analytics and risk in the financial services practice at The Execu|Search Group, a recruitment firm.
He says most firms prefer candidates with a Ph.D. in statistics, mathematics or computer science. “A lot of successful candidates have heavy programming skills – most Ph.D.s have experience working in C++ and the Python environment. It used to be Matlab, but now most firms are using Python.”
Hedge funds will also hire candidates right after graduation. Tang said Two Sigma recently hired a candidate with a Ph.D. from Princeton and internships at Google and Apple at a hefty starting salary.
The pay in data science is huge
“If a candidate’s got a Ph.D. in the right subject from Stanford or Yale and internships at Apple and Google or another Silicon Valley giant, they’ll get an offer in the $350k range right off the bat,” Tang said. “Most of these go back to the type of research that they’ve done, which machine learning especially in demand.
“Some do statistical analysis, data processing or imaging, but with the right type of research, hedge funds will generally make a standard offer between $300k and $400k all in for recent Ph.D. graduates,” he added
It’s not just hedge funds
Nor is it just hedge funds that want data people: long only funds and venture capital funds are chasing them too.
Traditional long-only asset managers such as mutual fund firms are targeting this same pool of fintech and quant talent. Traditional fundamental asset managers are particularly interested in hiring data scientists, said Reshma Ketkar, director and the head of the long-only investment professionals recruiting practice at Glocap.
“These data scientists are responsible for gleaning insights from big data and acting as another input into the investment process,” she said. They are not writing trading algos and they are not replacing human jobs.”
These traditional asset managers still invest based upon a fundamental view on the company, considering cash flows, valuations and the effectiveness of the management team, among other factors, but the data scientists are tasked with finding information that could be additive to the investment process, Ketkar said.
Fund firms such as AllianceBernstein, Fidelity and Goldman Sachs Asset Management have all hired data scientists as a supplement to their investment teams. An increasing number of fundamental hedge funds are also considering such a structure.
“The trend for data scientists crosses historically quant trading hedge funds and fundamental investment firms,” Ketkar said. “They all want data scientists, but on the fundamental investment firm side, they are an input rather than the main drivers of the investment process.”
There has also been plenty of recruitment action on the quant side of the asset management business – the programming languages that are in demand include Python, C++ and C#.
Photo credit: angusforbes/GettyImages