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