About Me
I’m a data enthusiast focused on turning complex information into clear, actionable insights.
What started as curiosity has evolved into hands-on experience building Python scripts, writing SQL queries, and creating clean, effective visualizations.
I enjoy solving real-world problems with data and helping others make informed decisions.
Outside of work, I enjoy hiking, gaming, and spending time with my family.
Skills Overview
Programming Languages
- Python
- SQL
Currently Learning
- Machine Learning
- Time Series Forecasting
Tools and Technologies
Python Libraries
- Pandas, NumPy, Scikit-learn, Matplotlib, Seaborn
- XGBoost, Random Forest, Statsmodels, PySpark, PyTorch
Modeling and Machine Learning
- Logistic Regression, Decision Trees, Cross-Validation
- Neural Networks (NN), Convolutional Neural Networks (CNN), Recurrent Neural Networks (RNN)
- Feature Engineering, Model Evaluation (RMSE, R², MAE, MSE, Confusion Matrix)
Data Analysis and Visualization
- Tableau, Excel, Quarto
- Jupyter Notebooks, Google Colab
Development and Version Control
- Git, GitHub, VS Code, Markdown
Databases and SQL
- MySQL, SQLite, PostgreSQL
- ERD Design, Data Cleaning, Joins, Set Operations
Web and Reporting
- HTML/CSS (via Quarto)
- GitHub Pages, Portfolio Development
Collaboration and Leadership
- Project Management
- Communication and Team Collaboration
- Leadership Experience (Digital Communications Supervisor at BYU–Idaho)
Practical Experience
Hands-on with SQL normalization, exploratory data analysis, feature engineering, and producing clean, web-ready reports using tools like Quarto and Jupyter Notebooks.
Want to see examples?
Visit the Projects page for detailed case studies and write-ups.