Goodnews Oseni

I’m a Chemical Process Engineer with a strong, data-driven focus on chemical process optimization—and I integrate AI/ML to make industrial workflows more efficient, safer, and cleaner. Over 5 years, I’ve applied machine learning and AI techniques to enhance chemical engineering workflows, improve production efficiency, and reduce waste.

In my most recent role as a Chemical Process Engineer (AI Integration) at Marathon Petroleum (Kenai Refinery), I led AI integration projects to improve predictive modeling for chemical production. I enhanced production systems with machine learning algorithms (15% efficiency gain, 25% waste reduction), and I implemented predictive maintenance models that improved uptime (12%) while reducing operational costs (10%).

Previously, as a Process Optimization Engineer at Taku Engineering, I used machine learning to support data-driven decision-making and delivered a 10% reduction in energy consumption in production systems. I also designed NLP models to analyze complex engineering texts, enabling faster problem-solving in R&D, and I owned the full model lifecycle from preprocessing through training, validation, and deployment.

As an AI Research Assistant with Alaska SBDC/UAA AI Resource Program, I supported research combining chemical engineering principles with AI methods and contributed to published papers. I developed deep learning models for chemical process simulation and optimization, improved predictive simulation accuracy by 15%, and strengthened industrial AI foundations through data annotation and feature engineering.