Enrique J. González García

Developed predictive algorithms using Sklearn, achieving 88% accuracy in sales forecasting; automated data cleaning, reducing manual effort by 35%.

Deployed network infrastructure for Intel’s new factory, supporting 500+ devices and ensuring 99.9% uptime. Trained and deployed ML models for predictive maintenance, reducing downtime by 18% and saving $200K/year. Data collection for the training and deployment of traffic analysis, anomaly detection and predictive maintenance ML models using Cisco AIOps.

Supported the CTO in backend activities: Optimized database queries, reducing load times by 40%; contributed to backend development using Flask and SQLAlchemy, improving system efficiency by 20%. Libraries used: Flask – Tkinter – SQLAlchemy.