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.
Your colleagues will include internationally recognized experts in machine learning research as well as highly experienced technology and finance professionals. The people who shape our company come from other backgrounds, too, including concert music performance, humanitarian aid, opera singing, sports writing, and BMX racing. You will be part of a team that loves to succeed together.
In addition to our enriching and collegial working environment, we offer highly competitive compensation and benefits packages, technology talks by our experts, a beautiful modern office, daily catered lunches, and more.
Your work will focus on the enduring challenges of 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 rapidly iterate on predictive models. Despite the complexity of these problems, market returns provide immediate and unambiguous outcome data for measuring success.
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.
- 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
- 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