AI / ML Quantitative Research Manager

Description

Graham Capital Management, L.P. is seeking an AI/ML Quantitative Research Manager to join our Quantitative Strategies team and lead collaborative AI/ML team research efforts. This individual will report into and work closely with our Chief Investment Officer of Quantitative Strategies to assess existing AI/ML capabilities, define a research agenda to improve AI/ML capabilities in current systematic trading systems, and create new AI/ML trading signals to complement and diversify the firm’s main strategies. The individual will maximize performance and competitiveness by utilizing advanced methods in quantitative analysis, risk management and portfolio optimization.

Responsibilities

• Work directly with the CIO-Quantitative Strategies to shape the long‑term AI/ML research roadmap
• Design, prototype, and develop production‑grade AI/ML models that ingest large‑scale alternative data sets to generate tradable signals to make existing trading signals more efficient, profitable and robust
• Work collaboratively in a research team environment, using common development tools to facilitate robust implementation of AI/ML research, production versions of trading systems, and ensure models are robust, scalable, and compliant
• Interact with other departments – data science, technology, operations, trading, marketing, and accounting - to ensure current and proposed ideas are implemented, monitored and executed efficiently and accurately
• Enhance the scalability and flexibility of portfolios to accommodate bespoke investment needs of clients
• Identify and integrate novel big‑data sources into the firm’s data pipeline
• Produce white‑papers, internal presentations, and external publications on AI/ML advances; deliver presentations at industry conferences
• Regularly present findings and ideas to management and investment committee
• Complete other projects as requested by senior management

Requirements

• PhD or MS in a quantitative field (e.g., Computer Science, Machine Learning, Statistics, or a related AI/ML discipline)
• 7+ years of hands‑on AI/ML research and production deployment in a quantitative or data‑science environment
• Strong understanding of systematic trading concepts; financial experience is strongly desired but secondary to AI technical expertise
• Demonstrated fundamental research experience in AI/ML (e.g., publications, conference presentations)
• Advanced programming experience in languages suited for quantitative research and strategy implementation
• Ability to synthesize complex topics into easily digestible verbal and written commentary
• Exposure to securities and derivatives markets and investment processes with knowledge in mid-to-low frequency systematic strategies (preferred)
• Experience managing a team of quantitative researchers is a plus