These days, ‘strats’ (a kind of hybrid of quants, programmers, data scientists and traders) have become some of the most in-demand people in finance. However, becoming a strat isn’t easy, even for those coming from the technology industry: you’ll need to be exceptionally good at math and programming. (It might help, too, to land a strat-focused qualification, such as a Master’s in Financial Engineering course.)
Carnegie Mellon University just released its employment report for graduates of its masters of science in computational finance course. Thirty percent of the class of 2019 went into ‘strats or modeling’ jobs, with another 29 percent going into quant research and 15 percent entering trading. Nearly 60 percent work in investment banks, with the remainder on the buyside, in fintech, consultancies or insurance.
Entry-level pay for strats is generous. In their first year of employment, Carnegie’s MSCF graduates earned an average of $125,000 in salary and signing bonuses. The highest-paid graduate earned a salary alone of $170,000. However, 76 percent of graduates work in New York, where the cost of living is high, which can squeeze the budgets of even the most highly-compensated finance and tech workers.
Richard Bryant, executive director of the MSCF program, said the course has changed significantly in the 25 years since its inception: “25 years ago, the program was all about the math needed for exotic derivatives and CDOs. Then, from 2007 to 2012, it was all about risk management. Since around 2013, the emphasis has been much more on data science and analytics, plus risk management and regulatory capital.”
Bryant said high frequency traders and hedge funds are also very interested in the strat course graduates. “Our students are self-selected as interested in quantitative finance: they don’t want to be a Google programmer (although a few end up that way) and this appeals to a lot of recruiters.”
The strat course is heavily over-subscribed, with 1,000 applicants for 100 places. “We need highly motivated students with top grades from good institutions,” Bryant says, adding that he also rejects applicants with poor communication skills. “We turn down some very strong quants either because their English isn’t satisfactory or because how they present themselves is going to be a problem.”
This article originally appeared in eFinancialCareers.