Romeo Ocon

Oil and Gas Industry Project

Data Engineering

• Supported the execution of economic and financial models developed by domain specialists, focusing on reliable data flow, configuration, and performance
• Integrated outputs from multiple interdependent models, ensuring consistent inputs, validated schemas, and reproducible results across runs
• Implemented sensitivity and scenario analysis pipelines to assess how changes in assumptions affected downstream financial outcomes
• Optimized execution and reporting workflows, achieving a 95% reduction in runtime and enabling faster decision cycles

Machine Learning & MLOps

• Implemented modern MLOps workflows including experiment tracking, reproducibility, and model lifecycle management
• Applied machine learning best practices for model evaluation, monitoring, and continuous improvement