Miguel Biron-lattes is a Postdoctoral Fellow and PhD statistician with a decade of experience applying Bayesian computational methods to real-world inverse problems and financial stability analysis. He combines deep academic research—publishing in top venues and developing GPU-accelerated, JAX-based gradient MCMC samplers—with practical consulting work mentoring graduate students and delivering statistical solutions across biostatistics, materials science, and medicine. His background in industrial engineering and roles in Chilean financial supervision and quantitative consulting give him rare fluency in large-scale data processing (SQL/R) and credit/market risk modelling. Currently he’s building a fully Bayesian surface-based muography inference pipeline that bridges geophysics and high-performance probabilistic computation. Colleagues value him for translating complex theory into reproducible, production-ready code and for mentoring the next generation of applied statisticians.
10 years of coding experience
9 years of employment as a software developer
Doctor of Philosophy - PhD, Statistics, Doctor of Philosophy - PhD, Statistics at The University of British Columbia
Master of Arts (M.A.), Statistics, Master of Arts (M.A.), Statistics at Columbia University in the City of New York
Bachelor of Engineering Science, Industrial Engineering, 6.4/7.0, Bachelor of Engineering Science, Industrial Engineering, 6.4/7.0 at Universidad de Chile
Contributions:4 releases, 6 commits, 7 pushes in 6 months
Find and Hire Top DevelopersWe’ve analyzed the programming source code of over 60 million software developers on GitHub and scored them by 50,000 skills. Sign-up on Prog,AI to search for software developers.
Request Free Trial
Miguel Biron-lattes - Postdoctoral Fellow at Simon Fraser University