Earll Abule

I’m a Computer Science graduate with experience in technical support, software development, and data science, including a 2-year technology-focused role delivering troubleshooting and system support in diverse environments. I combine strong problem-solving and communication to support users and ship practical technical solutions.

As a Technology Support Specialist, I improved key performance indicators and area goals by 20–50% through data tracking, goal setting, and process optimization. I designed and implemented a logistics tracking system using Google Sheets, Forms, and automation tools—improving cross-team coordination and reducing manual workload.

I also increased mission-wide logistics efficiency by ~70% and system reliability by ~50% by implementing structured workflows and automation. Earlier, I built a machine learning model for fruit quality classification at SegriTech, reaching >90% accuracy.

I enjoy turning messy inputs into usable outputs—automating data annotation workflows with Python (JSON processing) to double processing speed, and collaborating on web deployment and version control with GitHub. My undergraduate thesis explored a hybrid ML approach (SVM + clustering) with up to 97% accuracy and boxer-style classification using K-means.