About me
I recently completed a Master of Data Science (MDS) from the University of British Columbia (UBC), building on my undergraduate background in Economics and Statistics.
Prior to MDS, I spent three and a half years with Deloitte Vancouver’s Transfer Pricing practice where I developed and defended pricing strategies for multinational companies’ cross-border transactions. I found myself increasingly drawn to solving real-world problems through quantitative methods while working with complex financial and operational data, which led me to pursue further training in data science.
I am interested in applying statistical and machine learning techniques to drive better decision-making and business outcomes. Some of my recent work include building a business intelligence tool for a Vancouver-based dessert cafe to support daily operations planning, and co-developing a machine learning pipeline for UBC Cybersecurity to reduce response time to malicious email threats. You can learn more about my data projects here.
In my spare time, I enjoy playing soccer, pouring latte art, and snowboarding at local mountains.
Education
- Master of Data Science | UBC, 2025
- BA Combined Major in Economics and Statistics | UBC, 2020
Technical Skills
- Languages: Python, R, SQL
- Machine Learning: Regression, ensemble methods (Random Forest, XGBoost), clustering (k-means, DBSCAN), neural networks
- Statistics: Hypothesis testing, A/B testing, multivariate testing, non-parametric tests, power analysis, time series, Bayesian inference
- Data Visualization: Tableau, PowerBI, plotly, matplotlib, altair, ggplot2
- DevOps Tools: Git, GitHub Actions, Make, Docker
- Cloud Platforms: AWS (S3, EC2)