AI / ML Quantitative Research Manager

Grahamcapitalmanagement; Greater London; Hybrid; GBP 188,000 - 225,000; Full time

Benefits offered by this job

Discretionary annual bonus

Medical and life insurance

401(k) plans

Healthcare programs

Job summary

Graham Capital Management seeks an AI/ML Quantitative Research Manager to lead AI/ML research within the Quantitative Strategies team. You will report to the CIO of Quantitative Strategies, shaping the research agenda and creating AI/ML trading signals to diversify and strengthen the firm’s macro strategies.

The role requires a PhD or MS in a quantitative field, 7+ years of hands-on AI/ML work, strong programming skills, and experience guiding a research team.

Qualifications

• PhD or MS in a quantitative field is required.
• 7+ years of hands-on AI/ML research and production deployment.
• Strong understanding of systematic trading concepts; financial experience is desirable but secondary to AI skills.
• Demonstrated fundamental AI/ML research experience (publications/conference talks).
• Advanced programming experience in languages used for quantitative research.

Responsibilities

• Shape the long-term AI/ML research roadmap with the CIO-Quantitative Strategies.
• Design, prototype, and deploy production-grade AI/ML models that ingest large-scale data to generate signals.
• Collaborate in a research team to implement and productionize trading systems.
• Coordinate with data science, technology, operations, trading, and marketing.
• Enhance portfolio scalability to meet bespoke client needs.
• Identify novel data sources and integrate into the data pipeline.
• Produce white-papers and present at industry conferences; report findings to management.

Skills

PhD in quantitative field

7+ years AI/ML research

AI/ML research publications

Advanced programming

Securities knowledge / trading

Team management experience

Communication & synthesis

Cross-functional collaboration

Education

PhD or MS in quantitative field

Job description

Graham Capital Management, L.P. (collectively with its affiliates, "Graham") is an alternative investment manager founded in 1994 by Kenneth G. Tropin. Specializing in discretionary and quantitative macro strategies, Graham is dedicated to delivering strong, uncorrelated returns across a wide range of market environments. As one of the industry’s longest-standing global macro and trend-following managers, Graham remains committed to innovation, evolving its strategies through a robust investment, technology, and operational infrastructure. Graham harnesses the synergies between its discretionary and quantitative trading businesses to offer a broad suite of complementary alpha strategies, each built on the principles of thoughtful portfolio construction, active risk management, and diversification by design. Graham invests significant proprietary capital alongside its clients – including global institutions, endowments, foundations, family offices, sovereign wealth funds, investment management advisors, and qualified individual investors – reinforcing alignment of interests across all strategies.

The foundation of Graham’s sustainability and success is the experience and contributions of its people. The firm seeks to cultivate talent, encourage the diversity of ideas, and respect the contributions of all. In turn, each employee shares in the responsibility of strengthening those around them.

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

This role requires commuting into our Rowayton, CT, New York, NY, or London, UK office Mondays through Fridays. Please note that our central Quantitative Research team sits out of Rowayton, CT.

Base Salary Range

The anticipated base salary range for this position is $250,000 to $300,000. The anticipated range is based on information as of the time this post was generated and does not include any discretionary bonus or benefits (see eligibility below). The applicable annual salary or hourly rate paid to a successful applicant will be determined based on multiple factors, including without limitation the nature and extent of prior experience, skills, and qualifications. This wage range may be modified in the future.

In addition, the employee who fills this role will be eligible for a discretionary annual bonus, as well as a wide array of benefit programs, such as medical and life insurance, 401(K) plans, and access to other healthcare programs.

Notes:

No amount of pay is considered to be wages or compensation until such amount is earned, vested, and determinable. The amount and availability of any bonus, benefits, or any other form of compensation that a particular employee may be eligible for remains in the Company's sole discretion unless and until paid and may be modified at Graham’s sole discretion, consistent with the law.

Graham is committed to providing equal employment opportunity to all employees and applicants for employment without regard to their race, color, religious creed, gender, age, national origin, ancestry, alienage, citizenship status, handicap, disability, marital status, sexual orientation, gender identity, pregnancy, childbirth or other related conditions, military status, genetic information, or any other personal characteristics protected by applicable law. This policy applies to all terms and conditions of employment, including hiring, placement, promotion, layoff, termination, transfer, leave of absence and compensation.