Silvia Ruiz
About Silvia Ruiz
Silvia Ruiz serves as the Vice President and Data Scientist Lead at Chase, where she has worked since 2021. With a strong background in data science and a comprehensive understanding of the financial services industry, she has held various roles at prominent institutions including J.P. Morgan and Wells Fargo.
Work at Chase
Silvia Ruiz has held multiple positions at Chase, demonstrating a progressive career in data science. She currently serves as Vice President - Data Scientist Lead since 2021. Prior to this role, she worked as a Data Science Senior Associate in CCB Analytics from 2020 to 2021. Her earlier experience at Chase includes roles as a Data Insights Analyst and a Data Science Associate, contributing to various analytics projects within the organization.
Education and Expertise
Silvia Ruiz graduated from The Wharton School at the University of Pennsylvania with a Bachelor of Science in Economics. She furthered her education by completing a 26-week Data Science Immersive Course at Galvanize in 2018 and studied Mathematics at Columbia University. Additionally, she achieved an Analytics Edge certification from the Massachusetts Institute of Technology in 2019. Her technical skills include proficiency in programming languages such as Python, R, and SQL, as well as expertise in using Hadoop and Cloudera engines for data processing.
Background
Silvia Ruiz has a diverse background in the financial services industry, having worked at several prominent institutions. Her early career included internships at Bank of America and South Florida Educational Federal Credit Union. She gained significant experience at J.P. Morgan, where she held various rotational analyst positions. Her involvement with Management Leadership for Tomorrow as a Career Prep fellow further highlights her commitment to professional development in the finance sector.
Achievements
Silvia Ruiz has built a well-rounded career in data science and analytics within the financial services industry. Her comprehensive understanding of machine learning models and data science principles positions her as a leader in her field. Throughout her career, she has contributed to various projects that address the data needs and challenges of the financial sector, reflecting her strong technical foundation and industry knowledge.