Leonard Eun

Leonard Eun currently serves as the Applied AI/ML Director at JPMorgan Chase & Co., where he leads innovative initiatives at the intersection of quantitative finance and cutting-edge machine learning technologies. In this strategic role, Leonard provides research leadership for multidisciplinary working groups comprising quantitative researchers, data scientists, and technology specialists. His primary focus is on developing and deploying advanced ML models to enhance trading strategies, risk management, and client solutions. Leveraging his deep expertise in time series analysis, regression, classification, recommendation systems, and convex optimization, Leonard drives the integration of sophisticated algorithms into the firm’s core financial operations.

With a strong foundation in quantitative finance, statistics, and ML engineering, Leonard bridges the gap between traditional quantitative methods and modern applied AI techniques. His proficiency in programming languages such as Python and C++, combined with his knowledge of stochastic differential equations and statistical inference, enables him to craft robust models that address complex financial challenges. His experience with data mining, spectral analysis, and theoretical physics further enriches his approach, allowing for innovative solutions that push the boundaries of algorithmic trading and portfolio optimization.

At JPMorgan Chase, Leonard’s leadership is instrumental in advancing the firm’s capabilities in time series ML, ranking, and recommendation algorithms, ensuring that the organization remains at the forefront of financial technology. His work not only enhances predictive accuracy and decision-making efficiency but also fosters a culture of continuous innovation within the firm’s quantitative and technological teams. Through his expertise, Leonard Eun continues to shape the future of applied AI/ML in the financial industry, delivering impactful insights and transformative solutions.