Mohamed Dyab is a Senior Data & AI Engineer based in Paris with over a decade of experience building production-grade data platforms and ML systems across healthcare, legal, e-commerce and industrial domains. He has led end-to-end projects from founding data platforms and ETL pipelines on AWS and Snowflake to shipping MLOps solutions—most recently architecting an agentic AI procurement orchestration platform at Sanofi. His work includes cost-saving data quality tooling adopted at Air Liquide, automated contract NLP and knowledge-graph research that unlocked a six-figure tax credit, and performance-focused ML for advertising and video analytics. Comfortable as both individual contributor and tech lead, he combines infrastructure-as-code, CI/CD, and dbt-driven modeling to bridge product needs and reliable operations. A volunteer mentor for DeepLearning.AI programs, he pairs hands-on engineering with teaching and a history of entrepreneurship dating to a hardware IP core startup. Fluent in turning messy cross-functional requirements into auditable, scalable pipelines, he often surfaces business value through measurable KPIs and automation.
10 years of coding experience
11 years of employment as a software developer
Bachelor's degree Computer Systems and Engineering, Bachelor's degree Computer Systems and Engineering at Alexandria University
M2 Masters of Science in Informatics at Grenoble (MOSIG) Data Science, M2 Masters of Science in Informatics at Grenoble (MOSIG) Data Science at National School of Computer Science and Applied Mathematics of Grenoble
M1 Masters of Science in Informatics at Grenoble (MOSIG) Computer Science, M1 Masters of Science in Informatics at Grenoble (MOSIG) Computer Science at Université Grenoble Alpes
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