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?” Most of my projects start with a business question and then work through the data, modelling, validation, and interpretation needed to answer it.
📍 Toronto · 📊 Business & Data Analytics · 🐶 Usually working with my Chihuahua, Amiu, nearby
My projects cover pricing, customer risk, and resource allocation, using regression, machine learning, simulation, optimization, dashboards, and lightweight deployment.
15,332 listings · Regression · Tableau · Streamlit
Question: What actually drives Airbnb prices in Toronto?
I built a reproducible pricing analysis using a log-price OLS model, feature engineering, an interactive Tableau workbook, and a Streamlit pricing tool. The final model achieved test R² = 0.619. Property format and bathroom setup were associated with larger price differences than smaller operational features.
View the project · Open Tableau dashboard · Try the pricing app
95,824 orders · Classification · CatBoost · LightGBM
Question: How early can a business identify an order that is likely to end in a negative review?
I compared risk models at two points in the order lifecycle. The LightGBM placement model gives the business more time to respond, while the delivery-stage CatBoost model is more selective and reaches ROC-AUC 0.768. I use the comparison to show how model timing affects the type of action a business can take.
7 centres · Monte Carlo simulation · Integer optimization · Decision analytics
Question: How should limited staffing and bed capacity be allocated when winter demand is uncertain?
I combined optimization with a 5,000-night Monte Carlo stress test under a $33,000 nightly budget. The optimized plan allocates 19 staff. At that level, staff can support 380 clients, compared with 301 physical beds, so bed capacity becomes the tighter constraint under high demand.
Analytics: Python · pandas · NumPy · scikit-learn · Statsmodels
Visualization & delivery: Tableau · Streamlit · Excel
Methods: regression · classification · clustering · model validation · Monte Carlo simulation · optimization
Before analytics, I worked in client-facing banking at RBC and TD. That experience is one reason I tend to look at analytics from the business side. I care about the model, but also about whether the result is understandable and useful to the person making the decision.
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
I'm always happy to connect with people working in analytics, banking, or data-driven decision-making.
LinkedIn: linkedin.com/in/lamberttan · Email: tanjianglin845@gmail.com