Hi, I'm Nathaniel 👋
Data Science Leadership · Bayesian Statistics & Causal Inference · Still Learning...
About Me
I'm an experienced Data-Scientist and Statistician helping organisations make better decisions through data and experimentation. Using my expertise in Bayesian methods, Causal inference and Probabilistic AI I've learned to drive impact across multiple industries. I share what i've learned here.
Recent Highlights
Building the Mechanism: Front-Door Identification with Bayesian SEMs
My talk for the Causal Data Science Meeting 2026. The front-door criterion identifies causal effects despite unmeasured confounding, but only if the mediator carries the whole effect. I argue the mediator should be built, not found, and show how to audit that construction with Bayesian SEMs in PyMC.
View SlidesPodcast Appearance on Learning Bayesian Statistics
Talking confirmatory factor analysis & Bayesian methods with Alex Andorra on Learning Bayesian Statistics.
ListenConsumer Choice models in PyMC Marketing
Market competition eats into companies revenue bottom lines. Understanding the effective drivers of win-rates improves company revenues. I implement discrete choice models and demonstrate how to model product differentiation with PyMC marketing.
View Post