Quantitative Researcher
Point72 is a leading global alternative investment firm led by Steven A. Cohen that invests in multiple asset classes and strategies worldwide.
You'll work with Python and machine learning on large datasets to develop mid-frequency alpha strategies for Cubist Systematic Strategies, Point72's affiliate that deploys computer-driven trading across equities, futures, and forex. Responsibilities span alpha idea generation, data processing, backtesting, optimization, and production implementation of systematic equity trading strategies. This is an early-stage product launch opportunity for a new portfolio management team.
Free Tailor for ATS: 10/10 runs left
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:
A new Cubist portfolio management team specializing in the systematic trading of equities is looking for a Quant Researcher whose core focus will be working on mid-frequency alpha strategies. Joining the team will provide a unique opportunity to be involved with the early stages of a product launch and develop within a growing team.
Responsibilities:
Perform rigorous and innovative research to discover systematic anomalies in the equities market
End-to-end development, including alpha idea generation, data processing, strategy backtesting, optimization, and production implementation
Identify and evaluate new datasets for stock return prediction
Maintain and improve portfolio trading in a production environment
Contribute to the analysis framework for scalable research
Requirements:
MS or PhD in a quantitative discipline
0-2 years of professional work experience
A background in financial markets is not necessary, but an interest in the field is essential
Proven expertise in Python and handling large datasets
Fluency in data science practices, e.g., feature engineering. Experience with machine learning is a plus
Highly motivated, curious, and critical thinker
Collaborative mindset with strong independent research abilities
Commitment to the highest ethical standards