Responsibilities • Conduct research and development of CTA strategies, including trend following, momentum, volatility, and cross-asset models. • Collect, clean, and analyze large-scale, cross-market datasets. • Design, implement, and maintain backtesting frameworks to validate strategy robustness. • Collaborate closely with project managers to translate research outputs into live trading signals. • Monitor and optimize existing models to enhance performance and stability. Requirements • Bachelor’s degree or higher in Mathematics, Statistics, Physics, Computer Science, Financial Engineering, or a related field; Master’s or Ph.D. preferred. • Solid foundation in statistics, probability theory, and time series analysis. • Proficiency in Python or C++ for large-scale data analysis and research. • Familiarity with CTA/quantitative strategies such as trend following, momentum, and volatility models. • Strong problem-solving skills, logical thinking, and the ability to work independently. Preferred Qualifications • Experience in quantitative research at a hedge fund, Commodity Trading Advisor (CTA), or systematic trading desk. • Familiarity with machine learning applications in time series forecasting or signal generation. • Knowledge of multi-asset and multi-market CTA frameworks.