Wei Min Li, Cmt
About Wei Min Li, Cmt
Wei Min Li serves as the Head of Fixed Income Data Analytics at Piper Sandler, bringing over a decade of experience in the US fixed income capital market industry. He holds a Bachelor of Science in Actuarial Science from the University of Illinois Urbana-Champaign and a Master of Science in Data Science from Northwestern University.
Work at Piper Sandler
Wei Min Li serves as the Head of Fixed Income Data Analytics at Piper Sandler, a position he has held since 2021. In this role, he focuses on data analytics related to fixed income markets. He also holds the title of Director at Piper Sandler, a position he has maintained since 2019. His work is centered in the Greater Chicago Area, where he leverages his extensive experience in the fixed income capital market industry.
Education and Expertise
Wei Min Li earned a Bachelor of Science degree in Actuarial Science from the University of Illinois Urbana-Champaign, completing his studies from 2005 to 2010. He further advanced his education by obtaining a Master of Science in Data Science from Northwestern University, where he studied from 2018 to 2020. His educational background supports his deep knowledge in market data, analytics, and financial modeling across various fixed income product verticals.
Background
Wei Min Li has over a decade of experience in the US fixed income capital market industry. Prior to his current roles at Piper Sandler, he worked as an associate at BMO Capital Markets in Toronto, Ontario, Canada, from 2014 to 2015. His career includes positions at top investment banks, where he developed expertise in fixed income analytics and data management.
Achievements
Wei Min Li possesses extensive knowledge in a variety of market data and analytics related to fixed income products. His experience encompasses financial modeling across multiple verticals within the fixed income sector. His contributions to the field are supported by his roles at leading investment banks and his academic achievements in actuarial science and data science.