(Bloomberg) -- How do you tap the savvy of 730,000 data scientists for financial markets? Offer them $100,000 in prize money and a chance to impress one of the most successful hedge funds in the world.
That’s what $38 billion Two Sigma is doing with its new partner Kaggle, a community of data scientists who collaborate and compete in writing machine-learning algorithms.
In a contest starting Thursday at noon, Kaggle’s quants will have three months to create a predictive trading model from four gigabytes of financial data provided by Two Sigma. Cash prizes go to the seven best performers. Two Sigma, which competes with Silicon Valley giants for a limited supply of data scientists, aims to raise their awareness of markets and job opportunities in finance.
“There’s a shortage of folks looking at economic data,” Kartik Raghavan, who runs Two Sigma’s business innovation and growth team, said Tuesday at the firm’s New York headquarters. “So the question we’re posing is, can we get more people interested in this?”
Two Sigma joins other firms hosting competitions and platforms to find the next generation of quants. WorldQuant, which manages $4.5 billion, runs the WorldQuant Challenge and collaborates with MIT in contests to build algorithms. Billionaire Steve Cohen’s Point72 Asset Management has invested in Quantopian Inc., an online platform whose about 90,000 coders create and run trading algorithms.
Kaggle was started by econometrician Anthony Goldbloom and engineer Ben Hamner six years ago to attract established and wannabe data scientists to predictive modeling and analytics competitions. Quants competing for the largest prizes have modeled the likelihood of patients to go to a hospital in the next year, optimized flight routes based on weather and traffic, measured cardiac functions and monitored species of plankton from images.
Kaggle has worked with finance firms in the past. The San Francisco-based company says its hook-up with Two Sigma marks the first time it’s asking users to develop algorithms in an environment that closely simulates financial markets, which generate mountains of time-series data. The quants, who might not have access to large amounts of financial data without the help of Two Sigma, won’t know what securities or even the asset class they’re evaluating as they hunt for predictive trading signals.
“If we asked them what data sets to collect they wouldn’t know where to start, but they are really good at finding signals,” Goldbloom said of Kaggle’s non-finance users in the interview Tuesday.
About 40 percent of “Kagglers” are based in the U.S., followed by the European Union, India and China, Goldbloom said. Scientists from Eastern Europe are among the top ranked, and the Kaggle meetup group in Moscow is its biggest globally, he said. The scientists work at firms such as Adobe Systems Inc., Microsoft Corp. and Apple Inc.
“Kaggle is a very effective way to get attention for your algorithm” as opposed to publishing an academic paper and waiting years for recognition, said Goldbloom, who previously worked at Australia’s central bank and treasury.
Two Sigma, one of the fastest-growing hedge funds, has notched robust returns partly by using machine-learning algorithms. The firm employs more than 1,100 people and added about 575 employees since the start of 2015. Raghavan said Kaggle, with its 730,000 members, is an “interesting source” for recruitment.
“It’s a way to get people comfortable with financial data,” he said, referring to professionals like genomists, physicists and other academics.
Data science, a hybrid of statistics and computer coding, is a fledgling occupation, with the University of Washington and Columbia University among the few institutions offering a degree in the subject. Kaggle contestants earn a ranking based on their performance in challenges. Raghavan said he’s even seen the rankings on resumes.
The top Kaggle performer in the Two Sigma contest wins $25,000, with six runners-up dividing the rest of the pot.
“We want to engage this community of people worldwide," Raghavan said.
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