Baptized Bayesian and raised in the school of statistical learning theory, my interest lies in answering economic and system-level questions, albeit without losing the perspective from machine learning. I currently work in healthcare, where I'm passionate about building space for human relationships. I still consult on the side, from how to use stats and machine learning, as well as impact evaluation and experiment design. I spent years teaching code and teaching statistics, at universities and at bootcamps. I love teaching because I love theory: I love probabilities and functional purity, linear algebra and testability, complex language models and beautiful databases, causal inference and evented infrastructure. Sometimes, I make movies.