Senior Member of Research Staff (London)

Overview

In this role you will lead high-impact ML research for financial market prediction and portfolio optimization, translating advances into production-ready solutions that influence live trading. You will work with renowned AI/ML and finance professionals to tackle challenging, data-rich problems and mentor peers while shaping the research-to-production lifecycle. The position offers a collaborative, curiosity-driven culture with strong work-life balance and global collaboration. You will have a strategic stake in delivering measurable improvements to risk management and trading performance, at scale.

Pay / Benefits

• Hybrid work environment
• Relocation and visa eligibility for qualified candidates
• Opportunities to influence billions in daily trades
• Collaborative research culture
• Work-life balance
• Access to leading-edge AI/ML resources

Responsibilities

• Oversee long-term, complex research programs with mission-critical impact
• Deliver large-scale projects that improve product performance and risk management
• Develop deep domain understanding of Voleon’s methodologies and data
• Prepare and evaluate new datasets for predictive efficacy
• Develop, validate, and productionize new models
• Design experiments to improve simulations and test models in live trading
• Build cross-functional relationships and may act as external spokesperson
• Communicate with stakeholders to drive progress and outcomes
• Mentor researchers, provide technical guidance and feedback
• Stay updated on cutting-edge academic research for domain applications
• Contribute to talent recruitment efforts
• Lead projects from basic research to productization and live validation

Key requirements

• 5-10+ years directing research projects and mentoring colleagues
• Ability to run multiple projects simultaneously and make design judgments
• Strong problem-solving, risk assessment, and abstraction skills
• Proven track record solving large-scale computing problems
• Expertise in modern statistical methods and machine learning as an applied researcher
• Strong mathematical abilities
• Production-level coding skills in Python and/or R
• Clear communication of complex technical issues and documentation
• Influence without formal authority and cross-team impact
• Interest in financial applications; finance background not required
• Ph.D. coursework; Ph.D. degree preferred

• Strong communication of complex ideas simply
• Cross-functional collaboration
• Mentorship and technical leadership
• Modern statistical methods
• Machine learning for finance
• Python

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