I’m an Upstream Oil & Gas Data Analyst with a background in environmental consulting and regulatory reporting, and a master’s degree in data analytics. I enjoy solving data problems and turning complex technical information into clear, practical insights, using data engineering, analytics, and machine learning to investigate upstream datasets and improve reporting workflows.
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.
A compact PyTorch ANN (8-32-16-1, 833 parameters) predicts entrained droplet fraction in vertical gas-liquid flow, benchmarked against linear regression and TabNet with 5-fold CV and SHAP. The ANN reached R² ≈ 0.90 (RMSE ≈ 0.09) vs. 0.27 for the linear baseline and 0.75 for TabNet, with SHAP rankings consistent with entrainment physics.
Topics: multiphase flow, PyTorch, SHAP, TabNet, model evaluation, engineering data.
View the repository
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.
Lake Effect Ledger – a Python CLI narrative game covering natural-gas accounting, hedging, liquidity, and evidence across nine playable chapters. Additional components and docs coming soon.
Notebooks from my M.S. in Data Analytics are in Grad School python scripts:
- Tumor classification using GBM markers – decision trees and feature analysis
- Two-phase flow pattern classification – KNN and Gaussian Naive Bayes
- EDA of Acute Kidney Injury (AKI) stage data
- Groundwater chemical concentration trends – Mann-Kendall trend analysis
- 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.