Wong LiangChuan

I used to focus on molecules and processes—now I focus on patterns and insights, designing meaningful interactions between data and decision-makers.

My career began in the pharmaceutical manufacturing industry, where I worked with experimental and process data to monitor performance, identify trends, and ensure consistency in highly regulated environments. Through this experience, I became increasingly interested in how data could reveal patterns, improve processes, and support better decision-making.

This curiosity led me to transition into data analytics. I completed the General Assembly Data Analytics Bootcamp, where I developed hands-on experience in Python, SQL, Excel, data visualization, and machine learning, applying the full analytics workflow from data cleaning and exploratory analysis to predictive modelling and dashboard development.

I enjoy combining analytical thinking with data storytelling to translate complex datasets into clear, actionable insights.

Some of my projects include:
• Money Laundering Detection — built classification models on ~1M transactions to detect suspicious financial activity in highly imbalanced datasets
• HDB Resale Price Prediction — developed regression models and pricing tool to estimate property values in Singapore
• EU Sales Analysis — analysed transactional sales data using SQL and built dashboards to uncover profitability drivers and customer segments
• Hotel Booking Demand Analysis — examined booking trends and cancellation risks to identify revenue leakage opportunities using SQL and Tableau

These projects reflect my interest in using data to solve real-world business problems.