DevOps engineer & data enthusiast with a background in mathematics, machine learning, and creative visualization.
- BA in Comprehensive Mathematics – University of Arizona (2008)
- MS in Electrical & Computer Engineering – University of Arizona (2019)
I build projects that connect data workflows, visualization, and cloud engineering — turning raw data into insights and real products.
My portfolio balances workflow-heavy case studies with product-focused dashboards and creative explorations.
| Project | Focus Area | Workflow Signals | Product Output |
|---|---|---|---|
| Customer Churn Prediction | Full data pipeline & workflow | .github/ templates, issues, milestones, branching history |
SQL cleaning → Python modeling → Tableau dashboard |
| LEGO Dataset Dashboard | Visualization & product delivery | Lightweight Git, minimal issue/PR workflow | SQL cleaning → PHP web interface → Tableau dashboards |
| AWS Cost Analyzer | Cloud cost analysis (FinOps) | Python scripts with clean repo structure | Synthetic AWS cost dataset → Power BI/Tableau dashboards |
| Visualizations | Generative & artistic analysis | Lightweight repo structure | Processing.org sketches + Python data science for creative visuals |
This project demonstrates a full end-to-end data workflow.
I built a churn prediction pipeline starting with SQL cleaning scripts, moving into Python feature engineering and modeling, and finishing with a Tableau dashboard for results visualization.
The repo is structured like a real-world product build — with .github/ templates, issues, milestones, and branching history — to highlight not just the analysis but also the Git workflow and project management practices behind it.
This project focuses on data storytelling and visualization.
Using the Kaggle LEGO dataset, I designed Tableau dashboards to explore theme popularity, set complexity, and color usage across LEGO history. A lightweight SQL + PHP web interface supports the data, and the project could be containerized with Docker for portability.
Unlike the churn repo, this one emphasizes product delivery (interactive dashboards) rather than a workflow-heavy pipeline — providing a complementary showcase of my skills.
This project highlights my FinOps and cloud cost analysis skills.
I generated a synthetic AWS billing dataset (services, accounts, environments, teams) and used Python for preprocessing and cost breakdowns. The results were visualized in Power BI and Tableau dashboards to surface KPIs like MTD spend, service-level costs, and team allocations.
The project demonstrates my ability to connect cloud infrastructure knowledge with data analysis to support cost optimization — a bridge between my DevOps background and data-focused career path.
This repo highlights my work in data and signal visualizations using both Python and Processing.org.
It includes experiments like K-Nearest Neighbor variations in Python as well as a wide range of generative animations in Processing — from sinusoidal waves, knot curves, and polygon spirals to gravity simulations, graph algorithms, and artistic distortions.
The collection blends data science, algorithmic thinking, and creative coding, showcasing how technical models can be transformed into engaging visual experiences.
