The computers are taking over hedge funds. While most hedge funds have struggled with redemptions this year and others face existential questions about their business models, quant hedge funds have emerged as the leaders of the pack.
While there's been little activity among other hedge fund strategies, quant funds have continued to bolster their ranks - albeit selectively - says Albi Satku, vice president of sales and recruitment at Correlation One, which hires data scientists.
“They may not hire a lot, because these firms are looking for a number of different factors in their quants, like problem solving skills, programming ability and an innate sense for understanding how to make money,” she says. “On the tech side, analytics, problem solving abilities and data engineering – knowing tools for maintaining and retrieving data are also very important [for candidates applying to quantitative hedge funds].
“I haven't found this to be a particularly good year in the hiring market, but I do think that things will change come the new year and the emphasis on quantitative analysis will be the driving factor,” she said.
Hedge funds don't really indulge in cyclical hiring and firing like investment banks, but instead lay off a large proportion of their workforce so they can move in another direction, says Matthew Robert, senior consultant of quantitative research and trading at Selby Jennings.
The most recent trends has been moving towards improving and growing their quantitative divisions. Places like Tudor and GMO are great examples of this, laying off 10% and 15% of their workforce respectively, Robert said.
“I don't think this round of cuts is cyclical – I think it’s a matter of restructuring, like what IBM and Intel went through when they had to refocus their business to compete with the technological demand in the new ‘big data’ economy,” Setku said. “However, maybe you can see it as cyclical as they will need to hire again, just not the same type of profiles they are used to seeing, but more on the analytics side where data is used to drive not only investment strategies, but also solutions to business problems.”
Hedge funds that employ systematic trading strategies such as AQR, Two Sigma and Citadel are always pushing for good talent.
“The hot talent in the industry right now is in the quantitative research and trading space – and has been for some time,” Robert said. “Hedge funds are looking for Ph.D.s in a hard science that can bring new, improved ideas to the table, which comes in the form of complex predictive models.”
More specifically, the most wanted skill right now is machine learning, a skill that talent from places like Google, Facebook or Amazon will typically have, he said.
Most recently, Robert’s firm has placed fresh Ph.D. candidates with the titles “quantitative researcher” that are getting $100k-$120k as their base salary with a discretionary bonus on top. Quantitative portfolio managers that are seeing a base in the $200k range and approximately 10% of their PnL, the portfolio’s current value minus its previous value.
Successful Ph.D. graduates can see around $150k their first year out of college, whereas experienced portfolio managers can see more than a million dollars with good performance, Robert said.
Hedge funds are also hiring data scientists. Setku says that data scientists earn base salaries ranging from $105k to $110k with 15%-20% bonus potential. These were people who have had some type of research experience in the past and did a boot camp or graduate program to gain the skill set of a data scientist – programming and working with data.
On the hedge fund side, compensation varies greatly, as some like to keep their fixed costs low, so they will cap salaries while compensating individuals for their performance with a bonus that can range from 50% to 100% or more, she said. Hedge funds typically pay more, because they're looking for very specific skill-sets.
“There is still a mismatch in the market in terms of what firms are looking for and what talent is actually out there,” Setku said. “Back in the day on the sell side, a quant would do modeling and someone who could implement the model put it into the production – now they want someone who can program and be mathematical, and now that markets and margins are a bit tighter, they want people who have an innate sense to smell money."
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