About
Computer scientist (MSc, UBA, 2017), Specialist in mathematical statistics (UBA, 2025) interested in the computational aspects of Bayesian inference — modelling statistical problems as programs and implementing inference algorithms such as MCMC and SMC.
Now
Statistical computing. Applied problems both in the Bayesian workflow of a production-level Mix Marketing Model based on Gaussian processes, and downstream tasks like constrained optimization and optimal experimental design.
Contributor to the SMC subsystem. See BlackJAX paper (arXiv 2402.10797), all PRs, and full contribution notes →.
Previously
Built data products end-to-end from the ground up. Exploratory analysis, data pipelines, analysis software, and close stakeholder collaboration across multiple iterations.
End-to-end development of NLP models for real-time production inference. PyTorch, Airflow, Kubernetes.
Software design and architecture, refactoring large codebases, SRE, technical debt management, and testing.
Computational cognitive science. Optimal experimental design for rational analysis of question selection in humans.
Open source
Powerful add-ons for the PyMC probabilistic programming library
ciguaran / statistical_rethinking
Notes for the Statistical Rethinking course, written in PyMC
Selected work
Technical focus