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The Voleon GroupThe Voleon GroupBerkeley, CA

Member of Research Staff

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

Skills

Machine LearningStatistical MethodsPythonRData AnalysisPredictive ModelingLarge-Scale ComputingFinancial Modeling

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