🎓 Economics Undergraduate @ UCalgary | Aspiring Data Scientist
My name is Bozhao Wang. I am a data science enthusiast with expertise in machine learning, predictive modelling, and statistical analysis. With a background in economics and statistics, my focus lies in applying quantitative methods to solve real-world problems across fintech, ESG, and urban economics domains. I’m actively seeking opportunities in data science, business analytics, and related roles!
Programming Languages:
- Python, SQL
Machine Learning & Statistical Modeling:
- Classification & Regression (Logistic Regression, Random Forest, XGBoost)
- Hyperparameter Tuning (GridSearchCV, RandomizedSearchCV)
- Handling Imbalanced Data (SMOTE)
- Model Evaluation (AUC, Precision, Recall, Confusion Matrix)
Data Handling & Visualization:
- Exploratory Data Analysis (EDA)
- Data cleaning and preprocessing
- Data visualization
- Dashboard development (PowerBI, EXCEL)
Tools & Platforms:
- GitHub
- Jupyter Notebooks
- VS Code
- Microsoft Excel
- Power BI
- Credit Risk Prediction Using Supervised Machine Learning Model
Built and compared supervised learning models to predict credit card default using imbalanced financial data. Applied SMOTE oversampling and model evaluation metrics to enhance predictive performance and support risk assessment strategies. - Urban System Revenue Prediction with XGBoost (DSMLC Competition)
Applied XGBoost regression modelling to predict municipal revenue in urban systems using infrastructure investment data. Feature engineering, log transformation, and model tuning achieved high predictive accuracy. - Quantify Energy Risk Case Competition 2025
Built classification models (Logistic Regression, Random Forest, XGBoost) to predict high-loss CAT events. Created an interactive Power BI dashboard with parametric triggers and strategic recommendations for renewable expansion. - Demographic Trends and Housing Analysis in Calgary (Capstone Project) Conducted regression analysis on Calgary's housing supply and population growth using historical census and building permit data. Identified key factors influencing demographic shifts and housing demands to inform urban planning strategies.
- Detecting COVID-19 Health Misinformation Targeting Older Adults
Developed and compared TF–IDF + Logistic Regression and fine-tuned BERT classifiers on COVID-19 tweets, evaluated cross-platform robustness on senior-focused Reddit posts, applied SHAP for interpretability, and used LDA topic modelling to uncover key misinformation themes.
- 💻 Currently Learning NLP & LLM.
- Advancing my skills in machine learning and Python
- 🎯 Open to hackathons, case competitions, and interdisciplinary collaborations
- 🚀 Open to collaboration and internships in Data Science, Business Analytics, or Applied Research.
- 📢 How to reach me: BozhaoWang24@gmail.com
