Quantitative Researcher

About Cubist

Cubist Systematic Strategies, an affiliate of Point72, deploys systematic, computer-driven trading strategies across multiple liquid asset classes, including equities, futures and foreign exchange. The core of our effort is rigorous research into a wide range of market anomalies, fueled by our unparalleled access to a wide range of publicly available data sources.

Role/responsibilities

• Perform rigorous and innovative research to discover systematic anomalies in global macro markets (futures, FX, etc.)

• Perform feature engineering with price-volume, order book and alternative data at intraday to daily horizons in mid frequency trading space

• Perform feature combination and monetization using various modeling techniques

• Manage the research pipeline end-to-end, including signal idea generation, data processing, modeling, strategy backtesting, and production implementation

• Maintain and improve portfolio trading in a production environment

• Contribute to the analysis framework for scalable research

Requirements

• • Background in mathematics, statistics, machine learning, computer science, engineering, quantitative finance, or economics

• • 2-6 years of signal research experience in macro trading as part of a trading team

• • Specialization in swaps, fixed income, or commodities trading a plus.

• • Prior professional experience with feature engineering, modeling, or monetization

• • Ability to efficiently format and manipulate large, raw data sources

• • Demonstrated proficiency in Python, R, or C/C++. Familiarly with data science toolkits, such as scikit-learn, Pandas

• • Strong command of foundations of applied and theoretical statistics, linear algebra, and machine learning techniques

• • Collaborative mindset with strong independent research abilities

• • Commitment to the highest ethical standards