The Voleon Group
Peter Boennighausen is a skilled Software Engineer currently working at The Voleon Group since July 2022, specializing in machine learning engineering using Python and R. Previously, Peter served as a Software Engineer Intern at the same company, focusing on cloud infrastructure for research jobs utilizing Python, AWS, and Terraform. Peter's experience also includes a role as a Software Development Engineer Intern at Amazon, where full-stack web development in Java was performed for monitoring research jobs on AWS. Additionally, Peter worked as a Summer Analyst at Matrix Capital Management Company, L.P., analyzing software companies for a hedge fund. Peter holds a Master of Science in Computer Science from Stanford University, obtained in March 2022, and a Bachelor of Science in Computer Science from the same institution, earned in June 2021. Education was completed at Bellarmine College Preparatory from 2013 to 2017.
The Voleon Group
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Founded in 2007 by two machine learning scientists, The Voleon Group is a quantitative hedge fund headquartered in Berkeley, CA. We are committed to solving large-scale financial prediction problems with statistical machine learning. The Voleon Group combines an academic research culture with an emphasis on scalable architectures to deliver technology at the forefront of investment management. Many of our employees hold doctorates in statistics, computer science, and mathematics, among other quantitative disciplines. 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 and Head of Research is Statistics faculty at UC Berkeley, where he earned his Ph.D. Voleon prides itself on cultivating an office environment that fosters creativity, collaboration, and open thinking. We are committed to excellence in all aspects of our research and operations, while maintaining a culture of intellectual curiosity and flexibility. The Voleon Group is an Equal Opportunity employer. Applicants are considered without regard to race, color, religion, creed, national origin, age, sex, gender, marital status, sexual orientation and identity, genetic information, veteran status, citizenship, or any other factors prohibited by local, state, or federal law.