Overview
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 pr
Full job description
Full Job Description
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:
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Perform rigorous and innovative research to discover systematic anomalies in the equities market
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End-to-end development, including alpha idea generation, data processing, strategy backtesting, optimization, and production implementation
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Identify and evaluate new datasets for stock return prediction
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Maintain and improve portfolio trading in a production environment
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Contribute to the analysis framework for scalable research
Requirements:
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MS or PhD in a quantitative discipline
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0-2 years of professional work experience
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A background in financial markets is not necessary, but an interest in the field is essential
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Proven expertise in Python and handling large datasets
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Fluency in data science practices, e.g., feature engineering. Experience with machine learning is a plus
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Highly motivated, curious, and critical thinker
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Collaborative mindset with strong independent research abilities
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Commitment to the highest ethical standards
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