At Novus Fuels, I coordinated an international cross-functional team working across data science, data engineering, machine learning, and software development. I used Python, SQL, ETL, Excel, and QGIS to structure and validate energy-sector data, including more than 20 years of historical records.
I reduced data-processing and reporting time by approximately 50% through automation and workflow improvements, and contributed to approximately 37% improvement in operational efficiency. I also used AI-assisted approaches for research and information processing, and supported ML and data science initiatives through data preparation and coordination.
Previously, at IntelliGas, I processed more than 1M industrial sensor readings per day and improved data workflows using Python, SQL, PostgreSQL, MS SQL, and APIs. Automation saved more than 150 labor hours per month, while data-driven monitoring and analysis contributed to approximately 15% less operational downtime.
