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Posted 23 mo agoFirst seen 23 d ago
Quantitative Researcher
Posted by Point72 on 2 December 2024, 700 days ago. Still on their Greenhouse board when we checked 15 min ago. Half of Point72's roles come down within 138 days.
What the posting is about
Join Cubist's new equity trading team as a Quantitative Researcher. Focus on mid-frequency alpha strategies, from research to production. No financial markets background required, but interest is essential. Python and data science skills needed.
Read out of the posting
LevelNot stated
Experience askedNot stated
EmploymentNot stated
LocationLondon
RemoteNot stated
Visa sponsorshipNot stated
SalaryNot published, and most postings do not
Posted2024-12-02
Found viagreenhouse, direct from their system
We saw it 23 months after it went up.
The posting, as the company wrote it
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
Copied from Point72’s own board, not rewritten.
Also open at Point72
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