Summary
Ash Tounsi is a Lead Data Scientist with a PhD in Interdisciplinary Data Science who blends academic rigor with product-focused AI engineering to deliver NLP and LLM-driven solutions at scale. With four years of experience across research and industry, Ash has built production ML and serverless infrastructures (AWS Lambda, Bedrock, RAG, vector embeddings) and led MLOps, RLHF, and document-AI initiatives used in enterprise settings. His research background in precipitation nowcasting, flood risk mapping, and reservoir management informs pragmatic climate-aware models and operational forecasting systems integrated into cloud HPC environments. Known for mentoring teams and bridging compliance, DevOps, and product needs, he’s equally comfortable fine-tuning GPTs for domain-specific tasks and designing pipeline observability. Based in New York, he brings a rare combination of atmospheric science fieldwork and deep learning engineering that drives socially and environmentally impactful AI products.
4 years of coding experience
7 years of employment as a software developer
Engineer's degree Data Science, Engineer's degree Data Science at ENSAE Paris
Engineer's degree Computational and Applied Mathematics, Engineer's degree Computational and Applied Mathematics at National Engineering School of Tunis (ENIT), University of Tunis El Manar
Bachelor's degree Mathematics and Computer Science, Bachelor's degree Mathematics and Computer Science at Preparatory Institute for Engineering Studies - El-Manar (IPEIEM)
Doctor of Philosophy - PhD Interdisciplinary Data Science and Civil Engineering, Doctor of Philosophy - PhD Interdisciplinary Data Science and Civil Engineering at Stevens Institute of Technology
German, Arabic, English, French