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The Voleon Group

Runs machine-learning hedge funds for institutions

Senior Member of Research Staff - Optimization

Quantitative ResearchConfirmed live in the last 24 hours
Full-time$300k - $325k /yrHybrid

About the Job

Requirements

  • The candidate must have 5–10+ years of related experience in numerical methods, optimization solvers, mathematical programming, convex and/or nonconvex optimization, including directing key research projects and mentoring colleagues.
  • The candidate must have expertise in stochastic control and reinforcement learning.
  • The candidate must be able to run multiple projects simultaneously and exercise judgment in selecting methods, techniques, and evaluation criteria for determining results.
  • The candidate must make well-reasoned design decisions, identify potential issues, and assess tradeoffs, risks, and the appropriate level of abstraction.
  • The candidate must have a proven track record solving large-scale computing problems.
  • The candidate must have expertise in modern statistical methods and a track record as an applied researcher.
  • The candidate must demonstrate strong mathematical abilities.
  • The candidate must have strong software development skills and production-level coding experience; Python and/or C++ are preferred.
  • The candidate must be able to communicate complex technical issues clearly and transparently, including through insightful documentation.
  • The candidate must be able to influence without formal authority and have a track record of influence beyond their team.
  • Interest in financial applications is essential; prior finance industry experience is not required.
  • Ph.D.-level coursework is required.

Responsibilities

  • Design, implement, and improve large-scale constrained optimization methods for trading decisions under forecasts, risk, costs, liquidity, and operational constraints.
  • Provide strategic vision and perspective to oversee work affecting complex systems and mission-critical areas.
  • Complete large-scope, highly complex projects that produce noteworthy improvements to product performance and risk management.
  • Develop a strong understanding of the company's domain and methodologies.
  • Prepare and analyze datasets to assess their predictive efficacy.
  • Develop, validate, and implement new models in production.
  • Design and conduct experiments to improve simulations and evaluate new models in a live environment.
  • Build collaborative relationships across functions and with key contacts outside the area of expertise, potentially serving as an external spokesperson for the organization.
  • Communicate and collaborate with key stakeholders at each stage, facilitating discussions about complex issues and advancing tangible outcomes.
  • Mentor other researchers and provide technical guidance, coaching, and feedback.
  • Stay current with academic research and identify novel approaches to apply to the company's domain.
  • Contribute to recruiting exceptional talent.

Desired Qualifications

  • A Ph.D. degree in a relevant field is preferred.
  • Python and/or C++ are preferred.

About the Company

The Voleon Group

Runs machine-learning hedge funds for institutions

The Voleon Group runs hedge funds for institutions such as pension plans and sovereign wealth funds, using machine-learning models instead of human judgment to choose every trade. It began live trading in 2008 as one of the early hedge funds to hand all of its trading decisions to machine-learning models. Those models comb through years of price and trading data for patterns that predict market moves, then trade automatically in stocks, bonds, futures, currencies and derivatives. Voleon earns management fees plus a share of the gains it makes for investors. A computer scientist and a statistician founded Voleon in 2007, and it is based in Berkeley, California, near the University of California campus.

Company size
201-500
Company stage
Not listed
Total funding
Not listed
Headquarters
Berkeley, CA
Founded
2007

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