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Hedge Funds
Quantitative Researcher
at Point72
GraduateNo visa sponsorshipPython
Posted 18 hours ago
No clicks
- Compensation
- Not specified
- City
- London
- Country
- United Kingdom
Currency: Not specified
Join a new Cubist portfolio management team focused on systematic equity trading to develop mid-frequency alpha strategies. You will perform end-to-end research and development including alpha idea generation, data processing, strategy backtesting, optimization, and production implementation. The role involves identifying and evaluating new datasets, maintaining production trading systems, and contributing to a scalable analysis framework. Candidates should hold an MS or PhD, have strong Python and large-data experience, and be motivated, curious, and collaborative.
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Quantitative Researcher Career
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Quantitative Researcher
Apply Now
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:
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
Apply Now
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About Cubist
\nCubist 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:
\nA 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:
\n- 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:
\n- 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
\n
\n
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Quantitative Researcher
at Point72
Back to all Python jobs
Hedge Funds
Quantitative Researcher
at Point72
GraduateNo visa sponsorshipPython
Posted 18 hours ago
No clicks
- Compensation
- Not specified
- City
- London
- Country
- United Kingdom
Currency: Not specified
Join a new Cubist portfolio management team focused on systematic equity trading to develop mid-frequency alpha strategies. You will perform end-to-end research and development including alpha idea generation, data processing, strategy backtesting, optimization, and production implementation. The role involves identifying and evaluating new datasets, maintaining production trading systems, and contributing to a scalable analysis framework. Candidates should hold an MS or PhD, have strong Python and large-data experience, and be motivated, curious, and collaborative.
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Quantitative Researcher Career
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P72 Careers - Header
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Quantitative Researcher
Apply Now
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:
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
Apply Now
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About Cubist
\nCubist 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:
\nA 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:
\n- 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:
\n- 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
\n
\n
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