Notes on Data and Learning
My newsletter brings together working reflections on data, statistics, actuarial science, reproducibility, AI, and the ways we learn to work with them.
I explore the questions behind analytical work: how we frame a problem, what our models measure, and what changes when we put them into practice.
Selected issues
When Performance Is Not Learning
N.30 · 2 October 2026
How evaluation scores depend on the questions, data, metrics, and conditions used to produce them.
When the Model Changes the Data
N.29 · 18 September 2026
How decisions supported by a model shape future observations and create feedback loops in analytical work.
Before the Pipeline, There Is a Question
N.28 · 13 September 2026
Why defining an analytical question matters when AI helps prepare data, build workflows, and interpret results.