Description

As a Quantitative Research Analyst, will develop, monitor and maintain GCM’s systematic trading strategies. Daily activities will include forming investment hypotheses, finding and processing data relevant to the trading ideas, building mathematical models using various statistical and machine learning methods, putting the models into production, automation, comparing actual returns vs. simulation and monitoring model performance, as well as adjusting trading models in response to changing market environments. Specifically, will carry out the following duties:

Research and develop methods to make existing trading signals more efficient, profitable and robust.
Research and develop new trading signals that complement and diversify production strategies in terms of style, source of alpha and markets traded.
Research and develop portfolio construction and optimization methods to maximize performance while controlling risk, drawdowns and trading cost.
Enhance the scalability and flexibility of portfolios to accommodate bespoke investment needs of clients.
Follow robust research and development procedures to reduce differences between simulated and actual performance.
Work collaboratively in a research team environment, using common development tools to facilitate robust implementation of research as well as production versions of trading systems.
Interact with other departments – technology, operations, trading, marketing, and accounting - to ensure current and proposed ideas are implemented, monitored and executed efficiently and accurately.
Regularly present findings and ideas to management and investment committee.

Requirements

Master of Science degree in Physics, Mathematics or a related quantitative field and 2 years of experience in the job or a related position OR a PhD in Physics, Mathematics or a related quantitative field. Education, experience or training to include:

Probability and statistics, stochastic processes, signal processing, time-series analysis, mathematical optimization, and machine learning.
Translating academic ideas into code (Python, MATLAB).
Working on in-depth research projects in a collaborative data-drive research environment.

Location : Graham Capital Management, L.P., 40 Highland Avenue, Rowayton, CT 06853. This role requires commuting into our Rowayton, Connecticut office Mondays through Fridays, 5 days per week.

Salary : The anticipated salary range for this position is $215,000 to $230,000. 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.

Apply : On our website at: grahamcapital.com/careers.aspx or Send resume to HR@grahamcapital.com (Reference Job Code: 9686090).

*** This job is eligible for the Employee Referral Program.