Marco Fernandez

I’m a Data Science student at UCA (expected 2026), and I’m focused on turning messy, operational data into reliable analytics that teams can act on. I currently develop ETL pipelines at ExxonMobil using Python, SQL, and Azure to power business analytics across field operations.

In my current internship, I build and maintain ETL pipelines integrating diverse field operations data (production, sensor, and operational sources) into centralized analytics environments. I also deliver clean, structured datasets to the business analytics team to enable faster, more reliable decision-making across daily operations.

I bring hands-on experience building Deep Learning models with TensorFlow and PyTorch, along with broader exposure to NLP, time series, and classical machine learning. My goal is to grow as a junior professional by connecting strong data engineering fundamentals with practical ML development.

Beyond industry work, I’ve led practical lab sessions as an Assistant Professor for Numerical Methods (2025) and Introduction to Data Engineering (2026), guiding ~15 engineering students through hands-on MATLAB programming and numerical algorithms. I value clear communication, rigorous implementation, and analytical reasoning—skills I aim to bring to data science teams.