Passionate about transforming raw data into meaningful insight. I study Mathematics at the University of Waterloo with a deep focus on data science, data analysis, and business & financial analytics.
I'm Andrew — a Mathematics student at the University of Waterloo, originally from Toronto. I'm especially drawn to the full spectrum of data work: from cleaning and wrangling raw datasets to surfacing the financial and business insights that actually move decisions.
Data science, data analysis, business intelligence, and financial analytics are the areas that genuinely excite me. I love the moment when a messy dataset resolves into a clear pattern — and even more, the moment that pattern tells you something worth acting on.
Outside of lectures, I enjoy jazz and band music and anchor myself in my Christian faith — both of which, in different ways, remind me that the most important things are worth pursuing with patience and precision.
An interactive single-page web app visualising 331 Old Testament prophecies and 253 New Testament fulfillments as a force-directed constellation graph. Built a Python/Pandas data-cleaning pipeline handling multi-reference merging, regex normalisation, and deduplication — paired with a cross-reference heatmap and chapter-level density charts across 22 prophetic categories.
Real-time smart building monitoring system using AWS IoT Core, Lambda, and DynamoDB to collect sensor data via MQTT. Published custom CloudWatch metrics for CO₂ and temperature, with multi-room dashboards and proactive environmental alerts.
A fully interactive data analysis dashboard enabling real-time filtering, summary statistics, and dynamic visualisations on uploaded CSV datasets. Supports numeric and categorical data with downloadable results — built to simplify investigation and support decision-making.
Designed and queried a relational sales database to surface revenue trends, customer lifetime value, and product performance metrics. Leveraged Inner/Outer Joins and aggregations, with indexes to optimise data retrieval efficiency.
Open to internship opportunities, research collaborations, or just a good conversation about data, analytics, and what the numbers are trying to say.