About the job
Voleon Securities, a new business within the Voleon Group, provides liquidity in securities markets. We apply state-of-the-art AI/ML techniques to construct our market making strategies. For nearly two decades, our affiliate Voleon Capital Management has led the hedge fund industry and worked at the frontier of applying AI/ML to investment management, becoming a multibillion-dollar asset manager. Voleon Securities builds on Voleon’s deep real-world experience applying ML to financial markets. Voleon Securities is looking for creative, entrepreneurial researchers who enjoy grappling with very difficult problems.
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 trading 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
Qualifications
Minimum
Background in modern statistical methods and machine learning with a track record as an applied researcher, preferably with experience in at least one of the following: optimal control, deep RL, deep learning, and causal inference
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)
Ability to solve large-scale computing problems
Eagerness to work in a fast paced and growing business
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
Preferred
Hands-on experience building successful liquidity providing strategies across asset classes preferred but not required