About the job
As a Senior Member of Research Staff, you will work at the forefront of modern statistical machine learning leading key projects focused on enduring challenges of financial market prediction and portfolio optimization. Your research colleagues have collectively published hundreds of academic articles in top-tier venues on machine learning, systems, and theory, and we meet regularly to stay current on the latest academic research and share ideas. Founded by two leading scientists Voleon supports a culture of curiosity and creativity. We do not silo our teams, and you will enjoy a healthy work-life balance while tackling hard problems.
Responsibilities
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
Qualifications
Minimum
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 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 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
Preferred
No preferred qualifications listed.