It’s long been a trope for quant and data jobs in finance that success is about mostly mathematics, data manipulation, and coding. Knowledge of the financial services industry and its products is seen as subsidiary to this.
Vacslav Glukhov, JPMorgan’s AI research director until March this year, and the bank’s former head of quantitative research for electronic trading, disagrees.
“If you are just working with data, you will sit in the corner forever as a quant who works with data,” says Glukhov. “I always encourage my juniors to go out and explore the bigger world of sales trading compliance risk and legal – to get to know how the whole organisation.”
Glukhov, who has a PhD from Stanford in electrical engineering, spent five years at JPMorgan after joining from Liquidnet, where he spent nearly a decade working on algorithmic trading products. He says people misunderstand the nature of quantitative jobs in finance, and that had he only known the “deep truth” early in his career, it would have saved him a lot of angst.
That truth isn’t just that you need to understand the broader context of your work as a quant, but that you need to network internally, says Glukhov. “If someone told me to develop my social skills, my knowledge of the corporate world and my institutional and organizational capital, I think I would have succeeded a lot more than I have right now,” he reflects.
Ideally, he says, quants need to find themselves a good mentor. Absent that person, however, he has packaged up his knowledge and is selling it in his very own Udemy course on electronic trading, which includes both technical information for aspiring electronic trading professionals, plus his own perspectives on the future of electronic markets.
Despite finding himself in an apparent career hiatus, Glukhov says quant jobs in financial services are still a good career. A frequent complaint now is that quant jobs are more boring than they were before the global financial crisis, when the role was all about structuring complex products. Glukhov disagrees. He points to initiatives like dynamic hedging, initiated by Hans Buehler, the former JPMorgan head of global equities analytics, who’s now co-CEO of trading firm XTX. He also points to the spread of electronic trading into new markets.
“Electronification is saturated in equities and futures trading, but there’s still huge potential in fixed income, plus there are smart contracts, blockchain, crypto and the application of machine learning and AI to modules in algos that deal with order placement,” says Glukhov. “Quant jobs are anything but boring.”
Glukhov says it’s quants rather than technologists in banks who should own the roll-out of machine learning techniques – they understand the models behind. However, if quants are to thrive he reiterates that they need to stop being quants alone. “It’s a kind of self-stereotyping,” he says. “Yes, people enjoy focusing on what they do best, but it’s better to have a broader world view and to understand how to bring more value.”
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