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Our client, a prestigious financial institution, is looking for a highly analytical and mathematically skilled Senior Quantitative Analyst to join their cutting-edge algorithmic trading division. This role is integral to developing, implementing, and refining sophisticated trading strategies that leverage data-driven insights and advanced statistical modeling. You will work closely with traders and technologists to identify market inefficiencies, design predictive models, and backtest trading algorithms. Responsibilities include researching and analyzing vast datasets to uncover trading patterns, developing robust risk management frameworks for algorithmic strategies, and optimizing trading execution logic. The ideal candidate possesses a deep understanding of financial markets, a strong command of statistical and machine learning techniques, and exceptional programming skills in languages such as Python or C++. You will be expected to stay abreast of the latest academic research and market trends to continuously innovate and enhance our trading capabilities. This hybrid role combines the benefits of collaborative in-office work sessions and focused remote work, allowing for both team synergy and individual deep work. Join a highly motivated team in the heart of Chicago, Illinois, US , and contribute to the firm's success in the competitive global financial markets. We offer a stimulating work environment, continuous learning opportunities, and a comprehensive compensation package. Key Responsibilities: Develop and implement quantitative trading strategies using statistical and machine learning models. Analyze large financial datasets to identify market trends and trading opportunities. Design, build, and backtest trading algorithms. Develop and manage risk management frameworks for trading strategies. Collaborate with portfolio managers and software engineers to integrate strategies into production systems. Optimize trade execution logic to minimize slippage and costs. Research and apply cutting-edge quantitative finance methodologies. Monitor and analyze the performance of live trading strategies. Present research findings and strategy proposals to senior management. Stay current with market microstructure and regulatory developments. Contribute to the firm's intellectual property through innovative research. Qualifications: Master's or Ph.D. in a quantitative field such as Finance, Economics, Mathematics, Statistics, Physics, or Computer Science. Minimum of 5 years of experience in quantitative analysis, preferably within algorithmic trading or asset management. Strong proficiency in programming languages like Python, C++, or R. Extensive knowledge of statistical modeling, time series analysis, and machine learning techniques. Deep understanding of financial markets, derivatives, and trading mechanics. Experience with large-scale data analysis and database technologies. Excellent problem-solving and analytical skills. Strong communication and presentation abilities. Ability to work effectively in a fast-paced, team-oriented environment. Experience with financial libraries and platforms (e.g., NumPy, Pandas, SciPy).