Quantitative Researcher
London
Point72
We invest in Discretionary Long/Short, Macro, and Systematic strategies. We’re inventing the future of finance by revolutionizing how we develop our people and how we use data to shape our thinking. Join our team to innovate, experiment, and be...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+ years of signal research experience in macro trading as part of a trading team
- 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
* Salary range is an estimate based on our AI, ML, Data Science Salary Index 💰
Tags: Computer Science Economics Engineering Feature engineering Finance Linear algebra Machine Learning Mathematics Pandas Python R Research Scikit-learn Statistics Trading Strategies
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