About

Lal Chand Verma is a highly accomplished Vice President and Regional Lead for the Data Science Group at Bank of America. With over 13 years of experience in the field of quantitative services, Lal is a seasoned professional who has a proven track record of delivering strategic solutions, automation of procedures, and implementation across various projects. In his current role, Lal is responsible for leading a team of data scientists who are working on machine learning models across the model development lifecycle. He is also leading a risk validation team that is working on SIMM Risk Validation for UMR. Lal is a key contributor to the development of fuzzy logic-based in-house tools that have been implemented for various use cases. He has won multiple awards for his innovative contributions, including the Innovation Award 2018 at the global level and another award for Fuzzy logic implementations. Prior to his current role, Lal held various positions at Bank of America, including Assistant Vice President and Senior Manager in Quantitative Services. In these roles, he led teams working on risk validation for UMR, SIMM methodology, and risk controls. He also set up and managed new groups, including the Client Valuation Group and the Data Science Group, which has started working on machine learning models, classification techniques, and robotics process automation. Lal holds a PGDM in Finance from the Indian Institute of Management, Lucknow, and an Integrated Masters and Bachelors in Mathematics and Computing from the Indian Institute of Technology, Delhi. He also participated in an International Student Exchange Program in Finance at the Ecole Supérieure de Commerce de Toulouse. Lal is a skilled data scientist with expertise in machine learning and a strong background in finance. He is a results-driven professional who is committed to delivering high-quality work and making a positive impact on his organization. Lal is a valuable asset to any team looking for a highly skilled and experienced data science professional.