Emma Grandgirard

Full-stack data scientist with experience across analytics, engineering, machine learning, and teaching, in both industry and academic research. Skilled in building end-to-end data pipelines, analysis tools, and machine learning models, with a focus on quality and usability. Experienced in biomedical research and applied data science, motivated by interdisciplinary collaboration and impactful challenges in science, technology, and society.

I have experience across industry and academia as a full-stack data scientist, working at the intersection of data engineering, analytics, and machine learning. After two years at BVA building large-scale data pipelines and predictive models, I began a PhD in AI for biomedical imaging, where I design end-to-end deep learning pipelines and open tools for biological research. I also teach computer science and data science at university level, and enjoy bridging disciplines to make data-driven approaches accessible and useful.

I hold a PhD in AI and biomedical data science (defence in November 2025), a Master’s in Data Science & Engineering from Université de Toulouse, and a Master’s in Management from TBS Education (Toulouse).