Conducts advanced statistical machine learning research focused on financial market prediction and portfolio optimization. Develops, validates, and deploys predictive models using diverse datasets in a collaborative research environment. Requires PhD-level expertise in ML and strong mathematical background.
Salary not listed
HybridML Engineering
About the role
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
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