Personal portfolio site showcasing my data analytics projects, technical skills, and career transition journey.
Business-focused Data Analyst with 3+ years in banking and a background in marketing and finance. I turn complex datasets into clear, actionable insights that drive smarter decisions.
Before completing General Assembly's Data Analytics Bootcamp, I worked across banking, marketing, and finance — most recently as a Relationship Manager at Standard Chartered and CIMB, where I advised clients and ensured regulatory compliance. Across every role, I found myself drawn to the data side: building reports, spotting patterns, questioning the numbers.
That pull eventually became a push, and I made the switch for real. Now I combine domain knowledge from financial services with technical skills in Python, SQL, and machine learning to solve problems where data can drive better decisions.
Selected work from the GA Data Analytics Immersive and personal projects.
Built a fraud risk scoring model combining transaction data with clickstream browsing behaviour. Achieved ROC-AUC > 0.95 with data-driven risk tiers capturing 85%+ of fraud.
Machine learning model predicting Singapore HDB resale flat prices for WOW! Real Estate Agency. Achieved R² = 0.88 with LightGBM across 150K+ transactions, with an interactive Streamlit price calculator.
SQL-driven retention analysis of 400K+ transactions across 40 countries — cohort analysis, churn detection, RFM segmentation, and CLV estimation with a Tableau Public dashboard.
Brief description of your fourth project. Personal project or GA coursework.
I'm open to data analyst opportunities and always happy to chat about analytics projects.