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The Voleon GroupThe Voleon GroupBerkeley, CA

Senior Member of Research Staff, Optimization

Lead optimization research applying large-scale constrained optimization and ML to real-time trading decisions. Requires 5-10+ years experience, strong math/ML background, production coding skills, and PhD-level coursework.

300k – 325k/yr
Hybrid5+ YOEML Engineering

About the role

Responsibilities

  • Design, implement, and improve large-scale constrained optimization methods that determine trading decisions under forecasts, risk, costs, liquidity, and operational constraints
  • Demonstrate strategic vision and perspective to oversee work that affects one or more complex systems and mission-critical areas
  • Complete large scope, highly complex projects resulting in noteworthy improvements to product performance and risk management
  • Develop a rich understanding of Voleon’s domain and methodologies
  • 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
  • Build collaborative relationships cross-functionally and with key contacts outside own area of expertise, with the potential to serve as an external spokesperson for the organization
  • Communicate and collaborate effectively with key stakeholders at each stage, facilitating meaningful discussions around complex issues and driving progress towards tangible outcomes
  • Mentor other researchers and provide technical guidance, coaching, and feedback
  • Keep up to date on the latest academic research to identify novel approaches to explore for application to our domain
  • Contribute to Voleon's efforts to recruit exceptional talent

Requirements

  • 5-10+ years of related experience in modern optimization techniques and algorithms directing key research projects and mentoring colleagues
  • Experience with numerical methods, optimization solvers, mathematical programming, convex or nonconvex optimization
  • Capability to run multiple projects simultaneously, exercising judgment in the methods, techniques, and evaluation criteria for determining results
  • Ability to make well-reasoned design decisions, identifying and proactively potential issues, tradeoffs, risks, and the appropriate level of abstraction
  • Proven success solving large-scale computing problems
  • Expertise in modern statistical methods and machine learning with a track record as an applied researcher
  • Evidence of strong mathematical abilities
  • Strong skills in software development techniques and production level coding (Python and/or C++ preferred)
  • Effective at communicating complex technical issues simply and transparently, including writing insightful documentation
  • Ability to influence without requiring formal authority, with a proven track record of influence beyond your team
  • Interest in financial applications is essential, but prior finance industry experience is not a prerequisite
  • Ph.D. level coursework is required, and a Ph.D. degree in a relevant field is preferred

Preferred Qualifications

  • Expertise in stochastic control, and reinforcement learning

Skills

OptimizationNumerical MethodsOptimization SolversMathematical ProgrammingConvex OptimizationNonconvex OptimizationStatistical MethodsMachine LearningPythonC++Stochastic ControlReinforcement Learning

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