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.
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
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