Summary
Emilien Schultz is a research data engineer based in Paris with 11 years' experience at the intersection of humanities and computational social science, blending training in applied physics and signal processing with a PhD in sociology. He develops and applies Python-based scientific programming, ML and data-visualization workflows to social-science and health research, contributing to dozens of peer-reviewed publications across institutions like Gustave Roussy, Sciences Po, IRD and CREST. Regularly teaching quantitative methods and Python to diverse audiences, he translates qualitative survey and interview work into reproducible data pipelines under an open-science ethos. Notably, his background—moving from ENS Cachan physics to sociological studies of research policy and medical perception—gives him a rare ability to frame technical solutions around institutional and societal questions.
11 years of coding experience
Diplome de l'ENS de Cachan, Parcours normalien physique appliquée (EEA), Agrégation de physique appliquée, Diplome de l'ENS de Cachan, Parcours normalien physique appliquée (EEA), Agrégation de physique appliquée at ENS Cachan
Doctorat de sociologie, Sociology, Doctorat de sociologie, Sociology at Université Paris-Sorbonne
M2, Logique Philosophie Histoire et Sociologie des Sciences (LOPHISS), M2, Logique Philosophie Histoire et Sociologie des Sciences (LOPHISS) at Université Denis Diderot (Paris VII) / University Paris VII