I'm a Master of Management in Analytics candidate at Queen's University with a background in Statistics and client-facing banking experience at RBC and TD.
I moved into analytics because I enjoy the part between “we have data” and “so what should we do?” My projects usually start with a practical question, then work through the data, modelling, validation, and interpretation needed to answer it.
📍 Toronto · 📊 Business & Data Analytics · 🐶 Usually working with a Chihuahua nearby (Her name is Amiu btw :P)
I’m especially interested in problems involving customer behaviour, pricing, risk, and business decision-making. I work mainly in Python, with experience across statistical modelling, machine learning, simulation, optimization, and BI.
15,332 listings · Pricing · Statistical modelling · Streamlit
What actually drives Airbnb prices in Toronto?
I built a reproducible analysis around a log-price OLS model and found that property format and bathroom setup explain much larger price differences than smaller operational features. The final model explains about 61.8% of log-price variation on the test sample.
View the analysis · Try the live pricing app
95,824 orders · Classification · Customer experience
How early can a business identify an order that is likely to end in a negative review?
I compared models at different points in the order lifecycle. The later CatBoost model performed better (ROC-AUC 0.768), while the earlier model gave the business more time to intervene. The interesting part was not simply which model scored higher, but when a prediction becomes useful enough to act on.
Resource allocation · Monte Carlo simulation · Optimization
How should limited staffing and bed capacity be allocated when winter demand is uncertain?
I combined optimization with a 5,000-iteration Monte Carlo simulation to stress-test capacity across seven warming centres. The analysis showed how the operational bottleneck could shift from staffing to physical bed capacity.
Python · pandas · NumPy · scikit-learn · Statsmodels · LightGBM · CatBoost
SQL · R · Excel · Tableau · Power BI · Streamlit · Git
Methods: regression · classification · clustering · model validation · Monte Carlo simulation · optimization
Before analytics, I worked in client-facing banking at RBC and TD. That experience still shapes how I approach data: a technically correct result is only useful if someone can understand what it means and make a better decision with it.
Outside the notebook, I’m usually exploring Toronto, travelling, or spending time with my Chihuahua.
🎓 Master of Management in Analytics — Smith School of Business, Queen's University
🔎 Exploring opportunities in business analytics, data analytics, customer analytics, and risk analytics
📍 Toronto, Canada