Ahmad Hassan

I've delivered data science and machine learning engagements for McKinsey & Company, British American Tobacco, Regeneron, and Transatlantic Reinsurance. My work spans pricing optimization, demand forecasting, document intelligence, and production-grade AI systems.

For a transatlantic reinsurance company, I built an Azure document intelligence and RAG platform that processed 2 million documents, reduced manual triage by 50%, and improved processing throughput by 70%. At Regeneron, I developed LLM and agentic AI capabilities supporting 10k+ users, including document QA powered by RAG and Milvus.

I've also built price-elasticity forecasting for BAT across Germany, New Zealand, and South Africa, achieving MAPE below 30% in most markets. In healthcare, I led breast cancer segmentation work that reduced radiology examination workload by 35% and achieved over 80% mAP on mammograms.

I bring hands-on depth across AWS, Azure, Kubernetes, Terraform, CI/CD, and model lifecycle management. I enjoy translating complex business problems into scalable, measurable AI products while leading teams and working closely with stakeholders.