Wall Street has woken up to the need to hire big data professionals. Technologists who can manage, link and explore data are in demand – and financial services companies are willing to dig deep for the right people.
“It’s all about the data, “ says Terry Roche, head of fintech research at Tabb Group, a U.S. capital markets analysis firm. “It’s even more so now. With the heavy push on regulatory compliance there is a need across the Street to aggregate data holistically.”
On Wall Street, data used to mean market data or reference data. Those still matter, but now recruiters are looking to fill new positions requiring a variety of data skills.
Top of the heap is the chief data officer (CDO) who can take control of the sprawling mess of systems in big investment banks and make it available for alpha and for compliance, said Roche. Those jobs can pay more than $1m, depending on the size of the firm.
“But it’s a pretty complex task. You need long experience and you have to understand a lot of different technical disciplines,” says Roche.
John Bottega was one of the first CDOs, working for Citi, Bank of America and the Federal Reserve, but now CDOs are all over the place both at the enterprise and line of business (LOB) levels. They earn half a million to a million a year, while data stewards typically make $400k to $600k.
Just below in the pay scale are the people who do the actual work of accessing data in different systems and bringing it together, perhaps through an interface layer or through extraction that leaves the data in place while make it interoperable with other programmes. Salaries can range from $150k to several hundred thousand dollars.
Firms are looking for data scientists who also understand operations, added Roche. The challenge is to pull data from different areas into one data model. The most successful understand the business they are supporting as well.
Machine learning is in demand because big data is just too complex for traditional analytics, Roche adds.
Data scientist demand
Patrick Flannery, co-founder and CEO of MayStreet, an advanced capital markets technology company, said firms are building systems that can find their own way around big data.
“There’s a whole new set of problems — how make sense of it? If you are really good at big data you can take an arbitrary question and you have the infrastructure to answer it in reasonable amount of time,” he says.
While those jobs are typically called data scientists, he prefers a term he heard from a client — market scientist. But unlike a data scientist in marketing, who may never have a clear idea of his impact, in finance the results are clear. An extremely good engineer can earn $500k to $750k, he said. “But there are not a lot of seats to sit in where you are doing actual engineering work making more than $500k.”
Firms are looking for hands-on people with high quality technical skills, said Tom Morgan, a managing partner at IT recruiters Pencom in New York, and they will even go outside finance to find them. Firms have also developed career paths that reward technologists who want to stick to technology and not take a management job. They don’t want top technical people sitting in endless management meetings.
“Rather than move them into management, they have compensation that rewards technologists who may mentor a few people at the same level as a managing director with salaries running from $250k to $400k.”