Summary
Daniel Yang is a data science and AI leader with over a decade of experience translating large, messy datasets into explainable, production-ready ML solutions across finance and research. Currently a Vice President at Bank of America, he has driven fraud, cybersecurity, and PII-detection models at scale and built resilient ETL pipelines integrating Hadoop, Teradata, Oracle and Splunk. His background as a PhD-trained quantitative social psychologist and former academic PI informs a rigorous, theory-driven approach to variable selection, causal insight, and reproducible analytics. Daniel is known for reducing big-data processing from months to hours, communicating complex findings clearly to stakeholders, and bridging research-grade methods with enterprise risk and regulatory frameworks.
8 years of coding experience
6 years of employment as a software developer
Master of Science - MS Social Psychology (Quantitative emphasis), Master of Science - MS Social Psychology (Quantitative emphasis) at National Taiwan University
Bachelor of Science - BS Electrical Engineering, Bachelor of Science - BS Electrical Engineering at National Central University
Doctor of Philosophy - PhD Social Psychology (Quantitative emphasis), Doctor of Philosophy - PhD Social Psychology (Quantitative emphasis) at University of Illinois Urbana-Champaign
English, Chinese