I’m an Upstream Oil & Gas Data Analyst with a background in environmental science and a master’s degree in data analytics. I use data engineering, analytics, and machine learning to investigate upstream datasets, improve reporting workflows, and support technical and commercial decision-making.
Outside of work, you’ll usually find me road cycling, lifting, or working on DIY projects .
- Upstream oil & gas analytics (wells, production, completions, economics)
- Data quality, reconciliation, and workflow automation
- Commodity & energy markets and applied machine learning
- AI-assisted software development and reliable developer workflows
Graduate capstone using neural networks to predict entrained liquid droplet fraction in gas–liquid flow.
Topics: multiphase flow, PyTorch, model evaluation, engineering data.
Repository and technical summary coming soon.
Interactive tools for learning commodity markets: automated quizzes and a narrative learning game around natural-gas trading, hedging, accounting, and risk controls.
Topics: FastAPI, Streamlit, SQLite, retrieval-augmented generation.
Selected components and docs coming soon.
- Broader upstream oil & gas domain expertise
- Commodity-market and risk-management knowledge
- More reliable AI-assisted development workflows
- Production-ready data applications and automation tools
The best way to reach me is through LinkedIn.
You can also DM me on GitHub.