I design and deliver end-to-end systems across data engineering, predictive modeling, and full-stack application development: extracting live data, building analysis-ready pipelines, creating and validating machine learning forecasts, and shipping structured web applications with database-backed CRUD workflows.
My background in aerospace testing and quality assurance shapes how I build: validate early, document clearly, and design systems that stay reliable as they grow.
Deployed applications, real-time data systems, machine learning pipelines, and end-to-end full stack solutions. Includes architecture, backend services, APIs, databases, and frontend integration with technical walkthroughs of how each system is built.
Predictive modeling, visual analytics, R, Python, Tableau, and data-driven decision systems. Includes academic research, applied projects, and production-grade analysis.
Professional experience, certifications, and education. A direct link to my current resume for recruiters, collaborators, and contract work.
CodexPrime is my full-stack Django portfolio showcasing data engineering, analytics, machine learning foundations, and quality-first software delivery—built around repeatable workflows, clear structure, and production-minded validation.
I design reliable SQL-first workflows (joins, aggregations, drilldowns) and Python-based data processing built for reproducibility and scale.
I develop models and analysis for prediction and segmentation—regression, clustering, and tree-based methods—with evaluation metrics and clear interpretation.
I build and present my work through CodexPrime itself: a structured Django application with clean navigation, project pages, and deployable, review-friendly outputs.
Grounded in aerospace test and QA: validate inputs, isolate defects, document clearly, and ship systems that stay consistent as complexity grows.
If you'd like to learn more about the architecture of CodexPrime or connect about data engineering, machine learning, full-stack development, or QA—reach out.