New York City Metropolitan Area
Graduated with a Master's Degree in Data Science, Neo has a solid background in Statistic Modeling, Machine Learning, and Deep Learning. During the practice at Valley National Bank, Neo developed a sophisticated Loan Decision Model and validated a Small Business Administration(SBA) Valuation Model from a third party. Neo is not only proficient in Python, SQL, R, and Tableau, but also has hands experience in ETL, data modeling, and model validation. Neo is a good leader and also a great collaborator in teamwork; a self-starter has strong critical thinking skill. Supervisors commented on Neo as "highly self-motivated" personal.
1. Auto loan decision model: Reduce 90% human labor for Auto Loan underwriting with 95% prediction accuracy. 2. Customer stickiness for closing branches: Analyzed the loss rate of local customers when a branch is closed. Help Executives make data-driven decisions. 3. Small Business Administration(SBA) Market Value Validation: performed both loan-level and portfolio-level valuation. Validated Level1Analytics(L1A)’s report. Reverse-engineer their model for valuation.