Responsibilities
:
Design and execute research experiments to develop innovative models and strategies, evaluating results rigorously. Develop production-ready code for live trading integration, collaborating with developers. Enhance research and trading infrastructure through machine learning methods, including data preprocessing, feature selection, model training, and backtesting. Monitor live trading strategies for performance issues such as covariate shift. Integrate external libraries into production code following best engineering practices. Optimize model training and backtesting using parallel, distributed, and cloudputing. Explore opportunities for strategy expansion across global futures products. Stay current with industry advancements through research,petitions, and onlinemunities.
Required Qualifications:
Academic Background: Master's or PhD in a STEM field (, Machine Learning,puter Science, Physics).Experience: 3+ years of applied machine learning experience in amercial or academic setting, or 3+ years in quantitative research or development in trading.Skills: Strong understanding of multivariate statistics, time-series analysis, machine learning, and optimization. Strong programming skills in Python, including libraries like NumPy, Pandas, and Scikit-learn. Familiarity with Q/KDB and Git. Strong mathematical ability in linear algebra and calculus.
We are an equal opportunity employer and value diversity at ourpany. We do not discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status. Job ID 4659249007
