Aymane Razik

• • Architected and deployed an AI-driven lead intelligence system (Execution Lead Control™ ) that qualifies and governs high-volume inbound leads, reducing unqualified contact rate by automating intent scoring at the demand entry point

• • Built full-stack internal CRM and operations platform using Node.js, React.js, and make.com automation pipelines to streamline workflows across sales, follow-up, and client reporting

• • Designed cybersecurity-first data architecture for handling sensitive real estate transaction data, implementing encryption, access controls, and audit logging

• • Integrated AI-powered analytics dashboards enabling data-driven property acquisition and client matching decisions

• • Developed features for a B2B SaaS platform, implementing RESTful APIs and front-end modules using Node.js and React.js

• • Collaborated in agile sprints, delivering production-ready code with full test coverage and documentation

• • Contributed to cloud deployment pipeline and participated in architecture review sessions

• • Contributed to NET.SHIELD, an ML-based intrusion detection system; trained classification models to detect and predict network attacks with high precision using labeled network traffic datasets

• • Performed feature engineering, model evaluation (precision/recall/F1), and threat pattern analysis on real network data

• • Documented findings and presented results to the university's ITS security team