HRB
Quantitative Analyst for a global Asset Management Firm (New York, NY)
HRB, New York, New York, us, 10261
Our client, a global Asset Management firm, is looking for a Quantitative Analyst.
Role/Responsibilities:
Research and develop execution algorithms for US and global equities in support of quantitative research and trading. Enhance and aid in the support of in-house quantitative algorithmic platform used by both discretionary and quantitative traders. Develop pre-trade transaction cost estimation models and help drive strategy on improvements. Contribute in the development of firm-wide transaction costs measurement. Build and maintain market data and transaction databases for research and analysis. Stay current and report on changes in market microstructure. Requirements:
Masters or PhD in Mathematics, Financial Engineering, Statistics, or other quantitative discipline. Outstanding financial engineering and statistical modeling skills. 3-5 years of hands-on experience at a financial institution, building models for quantitative trading strategies or algorithmic trading. Experience with Python, C++, and SQL. Experience with KDB and Linux are a plus. Experience working with large datasets. Comprehensive knowledge of US equity market microstructure. Knowledge of international equity markets and non-equity markets are a plus. Sense of ownership of his/her work, working well both independently and within a small collaborative team.
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Role/Responsibilities:
Research and develop execution algorithms for US and global equities in support of quantitative research and trading. Enhance and aid in the support of in-house quantitative algorithmic platform used by both discretionary and quantitative traders. Develop pre-trade transaction cost estimation models and help drive strategy on improvements. Contribute in the development of firm-wide transaction costs measurement. Build and maintain market data and transaction databases for research and analysis. Stay current and report on changes in market microstructure. Requirements:
Masters or PhD in Mathematics, Financial Engineering, Statistics, or other quantitative discipline. Outstanding financial engineering and statistical modeling skills. 3-5 years of hands-on experience at a financial institution, building models for quantitative trading strategies or algorithmic trading. Experience with Python, C++, and SQL. Experience with KDB and Linux are a plus. Experience working with large datasets. Comprehensive knowledge of US equity market microstructure. Knowledge of international equity markets and non-equity markets are a plus. Sense of ownership of his/her work, working well both independently and within a small collaborative team.
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