Senior Member of Research Staff, Voleon Securities

Responsibilities

• Develop a rich understanding of Voleon Securities' challenges and methodologies and propose research innovations and experiments to build, maintain, and optimize the models that govern our trading 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 trading environment
• Build collaborative relationships cross-functionally and with key contacts outside your own area of expertise, with the potential to serve as an external spokesperson for Voleon Securities
• 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 trading and market prediction
• Contribute to Voleon's efforts to recruit exceptional talent

Requirements

• 5-10+ years of related experience directing key research projects and mentoring colleagues
• 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 modern statistical methods and machine learning with a track record as an applied researcher, preferably with experience in at least one of the following: optimal control, deep RL, deep learning, and causal inference
• Evidence of strong mathematical abilities (e.g., publication record, graduate coursework, or competition placement)
• Strong skills in software development techniques and production level coding (Python and/or R 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