The Voleon Group
Solving large-scale financial prediction problems with statistical machine learning
Actively Hiring
Highly Rated
Work/Life Balance
Strong Leadership
Overview
Co-founded in 2007 by two leading scientists, The Voleon Group combines an academic approach to research with an emphasis on scalability and risk management to deliver cutting-edge technology at the forefront of the finance industry. Many of our leaders and employees hold doctorates in statistics, computer science, and mathematics, among other quantitative disciplines. We are committed to exemplary performance in all aspects of our research and operations, while maintaining a culture of intellectual curiosity and flexibility.
Voleon’s CEO holds a Ph.D. in Computer Science from Stanford and previously founded and led a successful technology startup. Our Chief Investment Officer/Head of Research is a Statistics faculty member at UC Berkeley, where he earned his Ph.D.
At Voleon, we approach investment management through the prism of machine learning, in which flexible statistical models are applied to the problem of financial prediction. Rather than having humans look at individual events within the marketplace, machine learning employs statistical algorithms capable of detecting persistent effects across large swaths of data. Besides financial markets, there is a wide array of other real-life applications for machine learning, from medical diagnosis to weather prediction.
Voleon’s CEO holds a Ph.D. in Computer Science from Stanford and previously founded and led a successful technology startup. Our Chief Investment Officer/Head of Research is a Statistics faculty member at UC Berkeley, where he earned his Ph.D.
At Voleon, we approach investment management through the prism of machine learning, in which flexible statistical models are applied to the problem of financial prediction. Rather than having humans look at individual events within the marketplace, machine learning employs statistical algorithms capable of detecting persistent effects across large swaths of data. Besides financial markets, there is a wide array of other real-life applications for machine learning, from medical diagnosis to weather prediction.
Industries
Financial Services
Finance
Venture Capital
Hedge Funds
Finance Technology
Researchers