Senior Data Scientist · Amazon · Seattle
Building systems that help teams make better decisions.
I work at the intersection of causal inference, experimentation, and generative AI — designing the methods and pipelines that turn data into product direction.
What I work on
Causal Inference
Estimating the true effect of decisions — not just correlations. DoubleML, synthetic control, uplift modeling.
GenAI Systems
Building and evaluating LLM pipelines that hold in production. Multimodal evaluation, LLM-as-Judge, vector search.
Experimentation
Designing A/B tests that actually change roadmaps. Power analysis, CUPED, guardrails, and when not to experiment.
Writing
Practice, written down.
Causal Inference
Causal Inference in Practice
From observational data to real decisions. A practitioner's guide to the methods, intuitions, and applications of causal reasoning — built from years of running these models at Amazon scale.
GenAI Systems
GenAI Systems & Evaluation
How to build, evaluate, and trust generative AI systems in production. From LLM-as-Judge frameworks to multimodal pipelines — learned building these at Amazon scale.
Experimentation
Experimentation Science
How to design, run, and interpret A/B tests that actually change decisions. Power analysis, guardrails, CUPED, and the organizational dynamics of building a culture of experimentation.
Background
9+ years at Amazon — from BI engineer to Sr. Data Scientist. I've shipped experimentation platforms, causal inference pipelines, and end-to-end GenAI evaluation systems. This site is where I document what I've learned.
Newsletter
Stay in the loop.
New pieces on GenAI, causal inference, and experimentation — when I publish them. No spam.
Get in touch
Questions about causal inference, GenAI evaluation, or experimentation? Happy to chat.