If there’s a candidate with a skillset that can be sold to multiple employers in multiple sectors in late 2020, irrespective of COVID-19, it is the person with an elite education in data science and proven experience of extracting lucrative insights from real-world datasets. As a recruiter or a hiring manager, if you can find even one such data master, it is tantamount to hitting the jackpot. As a candidate who fits this description, you have the pick of employers.
This is especially true in banking and finance IT, where data scientists are present throughout organizations, from trading and research to HR. Data scientists are involved in everything from management decisions to cutting-edge machine learning projects.
But not all data scientists are made the same. The latest data science salary survey from recruitment firm Harnham puts entry-level data science salaries as low as £46,000 in the U.K. and $110,000 (for a data engineer) in the U.S.. By comparison, hedge funds can pay salaries as high as $200,000, but only for alpha generating data scientists at the top of their field. Dice’s own analysis of data-scientist salaries has shown a range of anywhere from $91,000 to roughly $170,000, depending on roles, experience and education; but such compensation can increase radically with specialization.
Some of the most desirable data science jobs in finance are in artificial intelligence. JPMorgan in particular continues to hire in London, New York and the Bay area for its A.I. research team focused on cryptography and broader finance. Goldman Sachs founded an A.I. research and development team under chief data officer Neema Raphael in 2017 and runs a parallel A.I. research team under MD Jeremy Glick. Raphael, who is charged with building Goldman’s data lake, is hiring.
Private equity firms are also in the game. Apax Partners, for example, recently poached Angelique Augereau, head of data science for treasury services at JPMorgan, to be its first-ever chief data science and analytics officer. Augereau, who will presumably be building a team at Apax, said she’s tasked with advising the fund’s portfolio of around 50 midcap companies on their “data and analytics journey.” Rival funds such as Cerberus have been on a similar journey for years already, and have hired heavily from banks to staff their data teams.
The flurry of data recruitment in finance has been accompanied by strong demand for data scientists in the consumer, tech, and consulting sectors, too. Desirable candidates have ample opportunities for productive job hopping as a result. Daniel Lin, a former JPMorgan derivatives trader who left to take a Masters degree in computational statistics, has worked for three different employers since 2017 in increasingly senior roles. Basiratpour says the most desirable data scientists are at Google or Microsoft, and are almost impossible to move.
Oliver Blaydon, the head of advanced analytics and risk recruitment at search firm Armstrong International, believes there’s an inevitability to data science recruitment that means demand is likely to remain robust throughout 2021. “It’s one of the busiest parts of the market,” he said. “Any bank or fund that has a hiring freeze will usually still be open to hiring in roles that involve data.”
A modified version of this article originally appeared in eFinancialCareers.