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Hedge funds and VCs are throwing money at ex-Bridgewater data scientists’ startup

Domino Data Lab, Nick Elprin, data scientists, data science, big data, data analytics, data analysis, Point72, Coatue, Sequoia Capital, Zetta Venture Partners, Bloomberg Beta, In-Q-Tel, CIA

Domino Data Lab is currently hiring in New York and Chicago.

It’s not secret that Bridgewater Associates has a quirky culture that doesn’t work out for everyone. 30% of its employees leave after the first two years and, after that, its founder Ray Dalio claims that most tend to stick around.

The hedge fund espouses “radical transparency” where employees are encouraged to both rate and challenge one another. For three former research specialists and data scientists who quit four years ago to start big data firm Domino Data Lab, some of that culture has rubbed off.

“It was our first job out of school where we were trained and for better or worse built our work habits,” said Thomas Robinson, the chief people officer in charge of HR, recruiting and office culture at Domino. “We borrowed many of the things we loved about Bridgewater’s high-performance culture. To create a high-performing team, you have to have trust and feedback – if you can’t provide honest feedback to individuals, then you miss out on opportunities to improve and build a stronger team.”

Domino is growing. It’s backed by Sequoia Capital, Zetta Venture Partners, Bloomberg Beta and In-Q-Tel, a nonprofit venture-capital firm that invests taxpayer money in startups developing technology useful to the Central Intelligence Agency, and just went through a $27m funding round in April led by hedge fund Coatue. A lot of this money is being poured back into the company to hire talented software engineers and data scientists, something Robinson acknowledges is a challenge.

“You see data science is one of the highest in-demand jobs, as there is still a dearth of data scientists – the talent market is pretty hot and can be difficult recruiting in finance,” Robinson said. “Software engineering and data science are incredibly sought-after positions for folks in finance, as data gets bigger and much more of trading and banking moves to algorithmic-based, the competitive landscape for tech talent has been a bit of a headwind for finance given the appeal of startups.”

“Finance is unique in that it can provide pretty aggressive compensation for folks, so we put a strong package together and communicated that with candidates,” he says.

Banks and hedge funds used to want to hire quantitative analysts, frequently PhDs in engineering, math, statistics or a hard science such as physics or chemistry. But the main problem financial services firms are facing right now is the data itself. It’s messy, unstructured and still difficult to use for alpha opportunities.

“In terms of how big data has impacted the financial services industry, it’s not just more, it’s far more complicated data sets, far more unstructured, messy data, for example, trying to look at Twitter data and infer housing data in India and build a trading algorithm around that, which is very complicated,” Robinson said. “There a recruiting push toward people who have both quant and hacking skills, the ability to cobble together systems and make quick and savvy insights with computer code.

Advice for aspiring financial software engineers and data scientists

Technology in general and data science in particular are great disciplines for students to study, because while some industries are going to adopt it quicker than others, everyone will eventually get how important it is for their business.

Nick Elprin, the CEO and co-founder of the firm, says just having a degree in a hot subject area is no guarantee of getting a job at a big hedge fund

“Don’t rely on what you’re learning in school – get yourself in a situation when you have real-world practical experience in a wide range of things,” he said. “I tried a bunch of different things, and I did an internship at Bridgewater even though I thought I wouldn’t like finance – I did it to check it off my list so I could say I had given it a shot.”

Previously a senior technologist at Bridgewater Associates, Elprin’s team designed and built the hedge fund firm’s next-generation research platform. His partners are also Bridgewater alumni: Chris Yang is Domino’s CTO, while Matthew Granade went back to work as a managing director and the chief market intelligence officer at Point72 Asset Management but is still on the board.

“We wanted to work together, but we all left before having a clear path or the idea of starting Domino,” Elprin said. “After we got out and were talking to companies about data science, we heard a lot of problems and challenges we felt well equipped to address.”

They cofounded Domino in 2013, and now it employs 60 people and counting.

“We’re trying to get ahead of that wave by developing new, more competitive product features and adding headcount to our field organization, hiring sales and customer success professionals at our offices in New York and Chicago,” he said. “We have a geographic concentration of financial services and insurance customers, so those are two good hubs. We want to hire people who have experience working in advanced analytics or data science, those types of technologies and use cases, even if they are coming from other industries.”

“Now that we have more capital to invest, we are also looking to hire product engineering specialists, primarily senior engineers with at least five-to-10 years of enterprise experience,” Elprin added. “We’re not doing mobile apps or web apps – it’s backend enterprise software, so we need technical product managers, people with experience designing and developing enterprise software product.”

Domino, Domino Data Lab, data scientists, data science, Bridgewater, Bridgewater Associates, hedge funds

Nick Elprin of Domino Data Lab



Photo credit: lesiar/GettyImages

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