🎓 Economics Graduate @ UCalgary | Energy & Business Analytics Enthusiast

My name is Bozhao Wang, and I am passionate about applying data analytics, economic research, and statistical modelling to solve real-world business and infrastructure challenges. My background in economics, forecasting, and large-scale data analysis has led me to work on projects involving energy infrastructure risk, urban development, and municipal investment analysis.

I have experience working with operational, regulatory, and economic datasets using Python, SQL, Databricks, and Power BI to support data-driven decision-making and strategic insights. My recent work includes developing a Liability Risk Index framework for oil & gas wells through the Society of Petroleum Engineers Data Science Mentorship Program and analyzing infrastructure investment impacts on housing markets through Data for Good Edmonton.

I am actively seeking opportunities in business analytics, energy analytics, economic research, and data-driven strategy roles!

Programming Languages:

• Python, SQL, RStudio, Databricks, Power BI, Microsoft Excel

Data Analysis & Forecasting:

• Statistical Modelling, Regression Analysis, Time Series Forecasting, Econometrics, Risk Analysis, Data Visualization

Data Engineering & Processing:

• Exploratory Data Analysis (EDA), Data cleaning & Validation, ETL Workflows, Data Integration, Feature Engineering, Dashboard Development

Business & Research Skills:

• Business Analysis, Economic Analysis, Trend Analysis, Research, Reporting, Decision Support, Strategic Thinking

Tools & Platforms:

• GitHub, Jupyter Notebook, VS Code, Power BI, ArcGIS, Microsoft Excel

• Liability Risk Index (LRI) for BC Oil & Gas Wells
  Developed a risk prioritization framework using Databricks, PySpark, and Power BI to identify high-risk oil & gas wells across British Columbia using operational, environmental, and financial indicators. Applied clustering techniques and spatial analytics to support regulatory and operational decision-making.

• 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.

• Civic Signal Program — Data for Good Edmonton Analyzed large-scale municipal property assessment and transportation infrastructure datasets from 2012 to 2024 to evaluate how infrastructure investments influence neighbourhood housing values and urban development trends. Applied econometric and spatial analysis techniques, including event-study difference-in-differences, hedonic regression, and spatial buffer analysis to support data-driven policy evaluation and strategic planning discussions.

• Energy & Infrastructure Analytics
• Business Intelligence & Forecasting
• Economic & Policy Analysis
• Risk Modelling & Decision Support
• Data Visualization & Dashboarding