Hachem Hamadeh

About

Industrial AI/ML practitioner with experience deploying real-time monitoring and anomaly detection in a regulated Sanofi vaccine manufacturing facility, including root-cause workflows, logging/alerting, and SOP-aligned validation—achieving ~90% faster anomaly detection. Also built Python/NLP-style automation to accelerate instrumentation & control documentation (~40% faster) and delivered end-to-end predictive analytics for an agri-food operations/distribution client using close operator and leadership feedback loops.

Experience

Education

Key Strengths

• Deployed real-time anomaly detection + root cause analysis into regulated vaccine manufacturing; cut anomaly detection latency ~90%
• Built scalable, reproducible AI/ML pipelines for high-volume heterogeneous sensor data across facility production lines
• Strong cross-functional execution with data engineering, IT, QC, validation/commissioning to deliver production-ready systems
• Systematic multi-domain troubleshooting (software/hardware/network) to isolate data dropouts and resolve pipeline/spec issues
• Python automation of I&C documentation workflows; reduced delivery time ~40% and improved consistency
• Effective on-site/operator collaboration and tight feedback loops to deliver predictive analytics/demand forecasting improvements
• Built repeatable experimentation framework to evaluate and narrow LLM tool choices for multi-million investment
• Translated technical pilot results into executive briefs with options, tradeoffs, ROI, and recommendations
• Stakeholder alignment across varied expectations; tight feedback loops to refine use cases and adoption
• Real-time LLM workflow debugging using logs/telemetry; standardized preprocessing and added fallback prompts to resolve inconsistent outputs
• Led technical seminar/workshop for 30+ engineers/scientists with hands-on, real-dataset demonstrations
• End-to-end ML pipeline scoping-to-implementation with operations/sales/distribution teams to drive adoption