Albert Bow
Quantitative Researcher - Chicago - $250,000 + bonus
Albert Bow, Chicago, Illinois, United States, 60290
Overview
My client is a leading proprietary trading firm based in Chicago, focused on leveraging advanced statistical methods, cutting-edge technology, and deep market insight to capture opportunities in global markets. They are currently seeking highly talented Quantitative Researchers to join their high-impact team and contribute directly to the development and optimization of algorithmic trading strategies.
Key Responsibilities
Research and develop systematic trading strategies across a range of asset classes, including equities, futures, and options. Analyze large, high-frequency datasets to identify inefficiencies and alpha-generating signals. Design and implement quantitative models for signal generation, risk management, and portfolio optimization. Collaborate closely with traders, engineers, and fellow researchers to iterate and refine strategies in a fast-paced environment. Conduct backtesting and performance evaluation using robust statistical techniques. Stay up to date with academic and industry research to drive innovation and maintain a competitive edge.
Required Qualifications
PhD or Master’s degree in a quantitative field such as Mathematics, Statistics, Physics, Computer Science, Electrical Engineering, or related disciplines. Exceptional programming skills in Python, C++, or similar languages; strong command of data analysis tools. Solid understanding of probability, statistics, optimization, and time series analysis. Demonstrated experience in signal generation, statistical arbitrage, or high-frequency trading (internships or academic projects acceptable for junior roles). Strong problem-solving skills with a rigorous, detail-oriented mindset. Ability to thrive in a collaborative, intellectually curious environment.
Preferred Qualifications
Prior experience at a hedge fund, proprietary trading firm, or quantitative research lab. Experience working with real-time data, tick-level analysis, or exchange microstructure. Familiarity with machine learning techniques and their application to financial data.
What They Offer
Opportunity to work with top-tier talent in a collaborative, meritocratic environment. Access to vast data resources and high-performance infrastructure. Competitive compensation package including base salary, performance bonuses, and benefits. Supportive culture that values innovation, transparency, and continuous learning.
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My client is a leading proprietary trading firm based in Chicago, focused on leveraging advanced statistical methods, cutting-edge technology, and deep market insight to capture opportunities in global markets. They are currently seeking highly talented Quantitative Researchers to join their high-impact team and contribute directly to the development and optimization of algorithmic trading strategies.
Key Responsibilities
Research and develop systematic trading strategies across a range of asset classes, including equities, futures, and options. Analyze large, high-frequency datasets to identify inefficiencies and alpha-generating signals. Design and implement quantitative models for signal generation, risk management, and portfolio optimization. Collaborate closely with traders, engineers, and fellow researchers to iterate and refine strategies in a fast-paced environment. Conduct backtesting and performance evaluation using robust statistical techniques. Stay up to date with academic and industry research to drive innovation and maintain a competitive edge.
Required Qualifications
PhD or Master’s degree in a quantitative field such as Mathematics, Statistics, Physics, Computer Science, Electrical Engineering, or related disciplines. Exceptional programming skills in Python, C++, or similar languages; strong command of data analysis tools. Solid understanding of probability, statistics, optimization, and time series analysis. Demonstrated experience in signal generation, statistical arbitrage, or high-frequency trading (internships or academic projects acceptable for junior roles). Strong problem-solving skills with a rigorous, detail-oriented mindset. Ability to thrive in a collaborative, intellectually curious environment.
Preferred Qualifications
Prior experience at a hedge fund, proprietary trading firm, or quantitative research lab. Experience working with real-time data, tick-level analysis, or exchange microstructure. Familiarity with machine learning techniques and their application to financial data.
What They Offer
Opportunity to work with top-tier talent in a collaborative, meritocratic environment. Access to vast data resources and high-performance infrastructure. Competitive compensation package including base salary, performance bonuses, and benefits. Supportive culture that values innovation, transparency, and continuous learning.
#J-18808-Ljbffr