Point72's Cubist Systematic Strategies seeks an experienced quantitative researcher to develop systematic trading models across fixed income, currency, and commodity markets. The role focuses on creating short-term to mid-frequency alpha strategies using advanced statistical and machine learning techniques.
Primary responsibilities include developing systematic trading models across FICC markets, managing research pipeline end-to-end from signal generation to production implementation, and performing feature engineering with various data sources for intraday to daily trading strategies.
The ideal candidate will have a strong background in mathematics, statistics, or related quantitative fields, with 2-5 years of macro quantitative trading experience. Essential skills include proficiency in Python, data science toolkits, machine learning techniques, and the ability to efficiently manipulate large, raw data sources.
Cubist offers a collaborative research environment with opportunities to work on cutting-edge systematic trading strategies, providing exposure to advanced quantitative finance techniques and the chance to contribute to sophisticated trading infrastructure at a leading financial firm.
