Member of Research Staff (New York)

Voleon is a technology company that applies state-of-the-art machine-learning techniques to real-world problems in finance. For more than a decade, we have led our industry and worked at the frontier of applying machine learning to investment management. We have become a multibillion-dollar asset manager, and we have ambitious goals for the future. As a Member of Research Staff, you will work at the forefront of modern statistical machine learning. Your research colleagues have collectively published hundreds of academic articles in top-tier venues on machine learning, systems, and theory, and we meet regularly to stay current on the latest academic research and share ideas. Founded in 2007 by two leading scientists (see management bios), Voleon supports a culture of curiosity, collegiality, and creativity. Your work will focus on financial market prediction and portfolio optimization. The behavior of financial markets is noisy and violates a number of classical statistical assumptions, and we’ve spent over a decade pioneering scientific advances in the application of machine learning techniques to this domain. You will work with a complex and diverse array of datasets to implement and iterate on predictive models. Predicting financial markets is an enduringly hard problem, but results are immediate and unambiguous. Years of academic training has prepared you for this moment. You won’t just conduct research, you’ll apply it on a daily basis, working with a team across the entire life cycle of applied research problems. Your work will span from basic research to productizing solutions and validating their efficacy in live trading. This role is a means to make a difference: you will help direct billions of dollars in trades daily while making an enduring impact on our field.

Relocation and work visa eligibility for qualified candidates

Responsibilities

• Develop a rich understanding of Voleon’s challenges and methodologies and propose research innovations and experiments to build, maintain, and optimize the models that govern our investment strategy
• Prepare and analyze new datasets to assess their predictive efficacy
• Develop, validate, and implement new models into production
• Design and conduct experiments to improve simulations and evaluate the success of new models in a live environment
• Communicate and collaborate effectively with other Members of Research Staff and Software Engineers at each stage, driving progress towards tangible outcomes
• Keep up to date on the latest academic research to identify novel approaches to explore for application to our domain

Requirements

• Background in modern statistical methods and machine learning with a track record as an applied researcher
• Evidence of strong mathematical abilities (e.g., publication record, graduate coursework, or competition placement)
• Interest in software development techniques and willingness to write production-level code (Python and/or R preferred)
• Ability to solve large-scale computing problems
• Eagerness to work in collaborative and diverse teams
• Interest in financial applications is essential, but prior finance industry experience is not a pre-requisite
• Ph.D. level coursework is required, and a Ph.D. degree in a relevant field is preferred