Regan C.H. Yin

About Me

I’m Regan C.H. Yin, an aspiring business analytics professional with a robust cross-functional background in data science, finance, and entrepreneurship.

Currently, I am pursuing my Master of Business Analytics (MBAN) at UBC Sauder School of Business (Class of 2026), awarded the prestigious Accelerated Career Scholarship for outstanding academic and professional achievements.

Previously, I completed a BBA in Information Systems and Finance with a specialization in Business Analytics at HKUST, where I was a recipient of the Tin Ka Ping Scholarship for Innovation and Entrepreneurship. I also attended UIUC Gies College of Business as a semester exchange student, focusing on Advanced Corporate Finance, Portfolio Management, and Derivatives.

Professional Experience

• Summer Analyst @ HKEX (Hong Kong Exchanges & Clearing Ltd.)
  • Designed real-time dashboards for senior executives using live data feeds.
  • Built the team’s first client monitoring system integrated with actionable analytics.
  • Conducted strategic analyses on Mainland A-share and GDR markets.
• Equity Intern @ CCB International Asset Management
  • Applied NLP sentiment analysis on financial news to support investment insights.
  • Evaluated the SPAC market under new regulatory environments.
  • Produced industry outlook reports for the semiconductor sector.
• Co-Founder & CFO @ DecenPay (dpAuth)
  • Spearheaded the creation of a DLT-based authentication ecosystem used in HR and logistics.
  • Secured over HKD$200K in early-stage funding from HKSTP and CityU.
  • Negotiated Federated Learning licensing with universities for privacy-preserving analytics.

Projects & Research

• Safety Incident Pattern Mining & Prevention Advisor — UBC MBAN Hackathon x Methanex & Google
  Built an end-to-end analytics platform for Methanex that transforms 200+ historical safety incident records into actionable prevention insights. Developed NLP-based clustering to identify recurring incident scenarios, an Early Warning Index combining near-miss frequency and severity, and a GenAI Frontline Advisor powered by Vertex AI (text embeddings, vector search) and Gemini that retrieves similar past incidents and surfaces vetted prevention guidance in plain language. Deployed on Google Cloud Platform with an interactive dashboard for safety managers and a natural-language advisor interface for frontline workers.

• Insider Behavior Detection in Earnings Calls
  Developed a multi-modal analytics framework combining FinBERT, WhisperX, and yFinance for identifying sentiment anomalies in earnings calls. Applied Granger causality and event study methodology to link executive tone with abnormal stock returns.

• Heart Disease Prediction via Machine Learning
  Built multiple ML models (Logistic Regression, KNN, Naïve Bayes) using the BRFSS 2020 dataset, incorporating cost-sensitive thresholds, achieving high recall for identifying high-risk individuals.

• US 2022 House Election Visualization
  Created a comprehensive time-series dashboard mapping electoral outcomes with polling, demographic, and turnout data. Demonstrated advanced data storytelling using Python and geopandas.

Skills

• Technical: Python, SQL, Tableau, Excel, Bloomberg, Linux, Whisper, FinBERT, HuggingFace, yFinance, GridSearchCV, Scikit-learn, PyAudioAnalysis
• Domain: Financial Markets, Risk Analytics, Predictive Modeling, Healthcare Data, Public Policy
• Soft Skills: Strategic Communication, Cross-cultural Collaboration, Presentation, Leadership, Entrepreneurial Thinking