Senior Member of Research Staff, Optimization

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 numerical methods, optimization solvers, mathematical programming, convex &/or nonconvex optimization directing key research projects and mentoring colleagues
• Expertise in stochastic control, and reinforcement learning
• 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
• Expertise in modern statistical methods 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
• 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