Zuleyka Benavides

I’m a data analyst with a B.S. in Bioinformatics, focused on applying Python, R, SQL, and machine learning to real-world datasets. I build end-to-end data pipelines, develop and evaluate predictive models, and clearly communicate findings to both technical and non-technical audiences—bringing biological research context for healthcare and life sciences work.

Recent projects reflect how I work end-to-end: I built a CNN Eye Disease Classifier in PyTorch that achieved 89% test accuracy across 16,242 fundus images, and I designed an automated Clinical Data Cleaning Pipeline to standardize and validate 10,000+ heterogeneous records. I’ve also delivered strong modeling results—like 98.7% accuracy with XGBoost for Phishing Website Detection—and used Tableau and ggplot2 to translate risk-factor insights (including diabetes risk) for academic audiences.