Daniel Jin
About Daniel Jin
Daniel Jin is a Business Intelligence Architect with a Master's degree in Econometrics and Quantitative Economics from New York University. He has extensive experience in developing data models, implementing A/B testing frameworks, and enhancing customer experiences through predictive modeling.
Work at Procede Software
Daniel Jin has been employed at Procede Software as a Business Intelligence Architect since 2018. In this role, he focuses on developing data-driven solutions that enhance business intelligence capabilities. His responsibilities include creating and implementing data models, as well as monitoring their performance to ensure optimal outcomes. Daniel collaborates with various teams to align data architecture with business strategies, contributing to the overall success of the organization.
Education and Expertise
Daniel Jin holds a Master's degree in Econometrics and Quantitative Economics from New York University, where he studied from 2015 to 2017. Prior to that, he earned a Bachelor's degree in Economics from San Diego State University, completing his studies from 2011 to 2014. His academic background equips him with a strong foundation in data analysis and economic modeling, which he applies in his professional roles.
Background
Before joining Procede Software, Daniel Jin gained valuable experience in various roles. He worked as a Research Assistant at San Diego State University from 2013 to 2014, where he contributed to research projects. He then served as a Junior Economist at New York University from 2016 to 2018, focusing on economic analysis. Additionally, he worked as an Analyst at Pharmapace, Inc for 10 months in 2015, where he developed skills in data analysis and predictive modeling.
Achievements
Daniel Jin has developed a custom A/B testing framework aimed at evaluating model quality and improving business outcomes. He has successfully coordinated with multiple functional teams to implement data models and monitor their outcomes. His work includes collaborating with product strategy management to create a comprehensive data architecture and implementing predictive modeling techniques to enhance customer experiences and drive revenue growth.