Summary
Hamman Samuel is a Senior Data Scientist with 13 years of experience building production-grade AI and data systems that turn messy, real-world signals into business impact. He combines a PhD-level research background with hands-on full-stack skills across Python, C#, JavaScript and cloud platforms (AWS, Azure, Snowflake) to deliver recommender systems, document intelligence, and LLM safety tooling. At Innodata he focuses on enterprise document processing and generative-AI reliability, having previously led optimization and analytics efforts for city-scale traffic systems and real-time recommenders at EA. His work spans the full ML lifecycle—modeling, CI/CD, Terraform/Docker deployments, and customer-facing dashboards—bridging technical depth with product thinking. Notably, he has applied ML to reduce player churn via toxicity detection and to detect fake health news, signaling a pattern of solving high-stakes, trust-sensitive problems. Based in Canada, Hamman blends research rigor with pragmatic engineering to ship resilient, auditable AI solutions for Fortune 500 clients.
12 years of coding experience
15 years of employment as a software developer
Doctor of Philosophy - PhD, Computing Science, Doctor of Philosophy - PhD, Computing Science at University of Alberta
Bachelor of Science - BS, Computer Science, Magna Cum Laude, Bachelor of Science - BS, Computer Science, Magna Cum Laude at American University of Nigeria
English, Urdu, Punjabi, Chinese