Yung-Hsiu Lai
(賴永岫)
Yung-Hsiu Lai
(賴永岫)
Research Assistant:
Marketing, University of Melbourne & University of Delaware
International Business, National Taiwan University
Economics, National Taiwan University
Research Interests:
AI (LLMs, Machine Learning, Deep Learning, NLP), Quantitative marketing, Consumer Behavior, Causal Inference, Marketing Decision Making, Time Series, Longitudinal Data Analysis
Work Experience:
Project Analyst, McKinsey & Company, 2024
Education:
M.S. (Statistics and Data Science) National Taiwan University
M.B.A. (Financial Engineering) National Taiwan University
B.B.A. (Quantitative Finance & Management) National Tsing Hua University
Contact: arvin.yh.lai@gmail.com ; LinkedIn
About Me
I am a researcher and practitioner specializing in quantitative marketing and consumer behavior. Currently, I am pursuing my second Master's degree in Statistics and Data Science at National Taiwan University and preparing for Marketing PhD applications for Fall 2026. My professional experience includes roles in the financial sector at Cathay Financial Holdings and CTBC Commercial Bank, consulting work at Mckinsey & Company, Nomura Research Institute, and project engagements with JPMorgan Chase and the Boston Consulting Group. These experiences have equipped me with a deep understanding of leveraging data-driven insights to create meaningful business impact.
My research spans quantitative marketing projects across Taiwan, Australia, and the United States. At National Taiwan University, I utilize my programming skills to manage and analyze complex big data operations, handling datasets at the terabyte scale. This includes extensive text mining and web scraping for the Economics and International Business departments. As a research assistant on joint projects between the University of Melbourne and the University of Delaware, I apply Large Language Models (LLMs) to marketing theory research and mine integrated data using EDGAR APIs, processing vast amounts of financial and marketing data to derive actionable insights.
My technical expertise includes data processing and analysis with Python, R, STATA, and SQL, enabling me to efficiently handle and interpret large-scale datasets. This is complemented by extensive experience in consumer behavior research and experimental design. Additionally, I served as a Project Analyst at McKinsey & Company, where I integrated my quantitative marketing knowledge with big data analytics to perform statistical modeling and data analysis on terabyte-scale datasets for clients. Fluent in Mandarin, Japanese, and English, I excel at bridging the gap between academic research and business applications. I welcome collaboration opportunities with those interested in exploring research in these areas.