Canvas Fundamental Research Group
Quantitative Researcher
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Experience
Early Career
Location
London
Focus
Systematic Investing
Business
Cubist
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
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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++. Familiarity 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
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