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The Voleon Group
- Alvis Wong
Alvis Wong is a skilled Software Engineer currently employed at The Voleon Group since October 2021, specializing in neural networks, LSTM, machine learning pipelines, and applied machine learning research. Prior to this position, Alvis contributed to various research projects as an Undergraduate Research Assistant at the University of Waterloo, enhancing BERT inference and developing significant tooling for generative models. Alvis has gained valuable industry experience through internships at Google, Zenefits, and Shopify Plus, where notable achievements include designing APIs, optimizing data workflows, and significantly improving performance for data analysis. Educational qualifications include a Bachelor's degree in Computer Science with a Business Option from the University of Waterloo.
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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.
