Rival banks are hiring technologists from Goldman Sachs
Goldman Sachs might want to keep a tighter grip on its technology talent. Since the start of this year, various of its senior technologists have found new jobs elsewhere.
The latest big name to move is Gavin Leo Rhynie, the former head of platform technology at Goldman in New York City, who has just joined JPMorgan as head of engineering and architecture for the corporate and investment bank (CIB) according to a memo sent by CIB technology head Mike Grimaldi. Leo Rhynie isn't JPM's only ex-Goldman hire though: JP also just poached James Kirby, a London-based vice president who spent seven years at Goldman with a focus on enterprise architecture and technology implementation.
Morgan Stanley has been checking out Goldman's talent too. As we reported earlier this month, the U.S. bank hired Michael Ballard, a VP in digital product at Goldman in New York who joined as an executive director in product strategy.
The exits come as Goldman itself ramps up technology hiring while preparing to cut costs by moving as many as half its technology jobs outside of London. Goldman's technology business is in a state of flux after the departure of leaders like Marty Chavez and Elisha Wiesel last year. However, Goldman technologists told us last week that they're super happy working for the bank, which is less political and pressured than big tech firms, gives them plenty of flexibility and is a better environment than most other places in finance.
Banks are big spenders on technology with JPMorgan, Bank of America and Citi spending the most. Citi is also hiring senior technologists externally: the bank just recruited James Linnett as CIO of global functions technology from Bank of America, where he spent 18 years.
Not all the new technology hires have technology backgrounds. JPMorgan is setting up a new London machine learning centre run by Chak Wong, a former trader and structurer at SocGen, Barclays, Morgan Stanley, Goldman and UBS. Wong, too, is hiring associates. Goldman especially may want to keep a strong grip on its machine learning people in the City.
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