Quantitative Researcher High Frequency Equities (US Markets New York)
Location: New York HK China
Responsibilities
- Analyze diverse datasets across US equity and futures markets to identify quantifiable trading edges and discover actionable alpha signals in high and midfrequency domains.
- Conduct endtoend research including alpha factor mining feature engineering model construction backtesting and strategy optimization with realistic transaction cost and execution modeling.
- Design and run robust backtests walkforward validation and stress tests to ensure signal stability and economic significance.
- Collaborate with execution engineering and risk teams to translate research into productionready strategies and support live deployment/monitoring.
- Execute critical research initiatives that directly support trading decisionmaking and performance attribution.
Requirements
- Bachelors Masters or PhD in Statistics Physics Computer Science Mathematics or another quantitative field.
- Proven handson experience with highfrequency US equity trading (experience with ticklevel data microstructure order book dynamics and execution constraints is required).
- Proficiency in at least one programming language: Python (preferred) C C# MATLAB or R.
- Strong data engineering and numerical skills for handling large ticklevel datasets and building scalable backtesting pipelines.
- Ability to read and synthesize academic/technical English literature and rapidly learn new technical domains.
- Intellectual curiosity rigorous analytical thinking and structured problemsolving skills; strong attention to model validation and risk controls.
Preferred
- Competition awards (e.g. IMO/IPhO/ACMICPC) or strong contest performance.
- Publications in toptier peerreviewed journals or conferences.
- Experience with lowlatency systems colocation market data feeds and execution optimization techniques.
- Familiarity with cloud/container technologies and production deployment (Docker CI/CD etc.).
How to apply
- Please submit your CV and a brief summary of relevant HF experience including the markets/data you worked with example signals or strategies developed and any performance/production outcomes.
Quantitative Researcher High Frequency Equities (US Markets New York) Location: New York HK China Responsibilities Analyze diverse datasets across US equity and futures markets to identify quantifiable trading edges and discover actionable alpha signals in high and midfrequency domains. Conduct en...
Quantitative Researcher High Frequency Equities (US Markets New York)
Location: New York HK China
Responsibilities
- Analyze diverse datasets across US equity and futures markets to identify quantifiable trading edges and discover actionable alpha signals in high and midfrequency domains.
- Conduct endtoend research including alpha factor mining feature engineering model construction backtesting and strategy optimization with realistic transaction cost and execution modeling.
- Design and run robust backtests walkforward validation and stress tests to ensure signal stability and economic significance.
- Collaborate with execution engineering and risk teams to translate research into productionready strategies and support live deployment/monitoring.
- Execute critical research initiatives that directly support trading decisionmaking and performance attribution.
Requirements
- Bachelors Masters or PhD in Statistics Physics Computer Science Mathematics or another quantitative field.
- Proven handson experience with highfrequency US equity trading (experience with ticklevel data microstructure order book dynamics and execution constraints is required).
- Proficiency in at least one programming language: Python (preferred) C C# MATLAB or R.
- Strong data engineering and numerical skills for handling large ticklevel datasets and building scalable backtesting pipelines.
- Ability to read and synthesize academic/technical English literature and rapidly learn new technical domains.
- Intellectual curiosity rigorous analytical thinking and structured problemsolving skills; strong attention to model validation and risk controls.
Preferred
- Competition awards (e.g. IMO/IPhO/ACMICPC) or strong contest performance.
- Publications in toptier peerreviewed journals or conferences.
- Experience with lowlatency systems colocation market data feeds and execution optimization techniques.
- Familiarity with cloud/container technologies and production deployment (Docker CI/CD etc.).
How to apply
- Please submit your CV and a brief summary of relevant HF experience including the markets/data you worked with example signals or strategies developed and any performance/production outcomes.
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