Summary
Gustavo Landfried is a Senior Data Scientist and PhD in Computer Science based in Lausanne with a decade of experience applying Bayesian methods to causal inference across health, sports, education and gaming. He develops and maintains TrueSkill Through Time—state-of-the-art open libraries in Julia, Python and R—that deliver low-uncertainty, historically comparable skill estimates and run efficiently on modest hardware. At Mutt Data and his lab he advises multinationals and public-health consortia (including a major Chagas disease project) on probabilistic model evidence and decision-making under uncertainty. He also teaches and designs curricula in Bayesian causal inference, bridging social-science rigor with scalable computational methods. A co-founder of Plurinational Bayes, he uniquely combines ethnographic training with advanced inference engineering, routinely translating complex graphical causal arguments into actionable analyses.
10 years of coding experience
14 years of employment as a software developer
PhD in Computer Science, PhD in Computer Science at Universidad de Buenos Aires
English, French, Spanish