Hi there! I’m Yuanjun Lin. My interest in analytics and data science began with a simple curiosity: understanding the patterns behind complex systems and the often-overlooked phenomena that shape the world around us.
I earned my undergraduate degree in Data Science from Duke Kunshan University and later completed my M.S. in Operations Research at the University of California, Berkeley. Across both programs, I developed a strong foundation in statistical modeling, machine learning, optimization, programming, and data-driven decision-making, while also exploring applications in finance and risk analysis.
My interest in quantitative problem-solving started long before university. I began learning computer science and natural science topics in middle school, then gradually developed broader interests in social science and contemporary philosophy. That combination has continued to shape how I approach analytical work: I enjoy both the technical process of building models and the larger question of what those models can tell us about real-world systems.
Over time, my work has included data analysis, market research, technical consulting, and quantitative financial research. More recently, I have been developing Python-based research workflows for financial data processing, statistical and machine learning modeling, backtesting, factor analysis, and risk evaluation. I am especially interested in building practical analytical systems that can move from exploratory research to repeatable real-world applications.
Outside of technical work, I continue to value the human side of technology and research. I enjoy learning across disciplines, exploring new ideas, and contributing to projects and communities where analytical thinking can create meaningful practical value.
This site is a place for me to share my work, research, experiments, and ongoing interests across data, quantitative analysis, technology, and finance. Welcome to my corner of the internet!