Daniel Posada

Daniel Posada is a data scientist at Hagerty, where significant achievements include the development of a tree-based classification ML model with over 82% accuracy and expertise in utilizing Metaflow and AWS for improving model training efficiency. Prior to this role, Daniel served as an associate software engineer, gaining experience with Microsoft Azure and enhancing a Configuration Management Database (CMDB) which contributed to a 21% reduction in Mean Time to Resolve. Daniel's background also includes serving as a Customs and Border Protection Officer at the U.S. Department of Homeland Security, excelling in various operational and customer service tasks. Additionally, Daniel has teaching experience from Sylvan Learning and IT support experience at Aldani Inc. Daniel holds a Bachelor of Science in Computer Science from Western Governors University and a Bachelor of Science in Chemistry from The University of Texas at Austin.