I am especially motivated by the development and implementation of software tools for Bayesian statistics and probabilistic modeling.
I am interested in exploring all dimensions of the Bayesian workflow, including prior elicitation, numerical methods for inference, diagnosis of sampling, evaluation and
criticism of models, comparison of models and presentation of results.
I collaborate with many Python open source projects for Bayesian statistics: ArviZ,
Bambi, Kulprit,
PreliZ, PyMC, and
PyMC-BART.
I teach Bayesian stats at UNSAM (Argentina).
I create resources to make statistics easier to grasp at Intuitive Bayes.
I help companies solve challenging business problems at PyMC-Labs