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akabzw24/README.md

πŸ‘‹ Welcome! I'm Bozhao Wang

πŸŽ“ Economics Undergraduate @ UCalgary | Aspiring Data Scientist | Future Business Analyst


πŸ‘€ About Me

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 data science, I specialize in using machine learning algorithms to extract insights from complex datasets and drive data-driven decision-making. I am actively seeking opportunities in data science, business analytics and related fields where I can apply my quantitative expertise and analytical skills to solve real-world challenges.


πŸ› οΈ Technical Skills

Programming Languages:

  • Python

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
  • Microsoft Excel
  • Power BI

πŸ“‚ My Projects

  • 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 & Building

  • πŸ’» Currently Learning NLP & LLM.
  • πŸ§ͺ Participating in national competitions:
    • National Mental Health Datathon 2025
    • First DREAM Target 2035 Drug Discovery Challenge
  • Advancing my skills in machine learning and Python

πŸ’žοΈ Collaboration Interests

  • 🎯 Open to hackathons, case competitions, and interdisciplinary collaborations
  • πŸš€ Open to collaboration and internships in Data Science, Business Analytics, or Applied Research.
  • πŸ“’ How to reach me: [email protected]

πŸ“« Connect with Me

LinkedIn

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  1. Credit-Risk-Prediction-Using-Supervised-Machine-Learning-Model Credit-Risk-Prediction-Using-Supervised-Machine-Learning-Model Public

    A machine learning project for predicting credit card default risk using supervised machine learning techniques like Logistic Regression, Random Forest, XGBoost. Applied SMOTE, and hyperparameter t…

    Jupyter Notebook

  2. Demographic-Trends-and-Housing-Analysis-in-Calgary Demographic-Trends-and-Housing-Analysis-in-Calgary Public

    Capstone Project conducted regression analysis on Calgary's housing supply and population growth using historical census and building permit data.

  3. covid-misinfo-nlp covid-misinfo-nlp Public

    Detecting COVID-19 health misinformation targeting older adults using TF-IDF, logistic regression, and BERT

    Jupyter Notebook

  4. quantify-energy-risk-case-2025 quantify-energy-risk-case-2025 Public

    Quantify 2025 Energy Risk & Insurance Case Modeling high-loss CAT events and developing parametric risk triggers to support renewable energy expansion. Includes ML code, writing report, and Present…

    Jupyter Notebook

  5. Urban-revenue-prediction-XGBoost Urban-revenue-prediction-XGBoost Public

    DSMLC Final Competition project using XGBoost to predict urban project revenue. Data provided by Urban Systems in Calgary.

    Jupyter Notebook