Normally Distributed

I have an unofficial rule on this blog: no listicles.

Ten days ago, I started building a diagram library from scratch.

A few months ago, I participated in a company-wide hackathon with a group of data engineers.

I've been spending a lot of time lately figuring out which AI tools to invest in.

I've been using Claude Code almost every day for over six months now, and the thing that surprises me most isn't how fast it is.

If you've been following AI news lately, you've probably heard about the viral rise of Moltbook.

I’ve been back at work for three weeks after seven-and-a-half months of maternity leave, and it genuinely feels like I've returned to a completely different industry.

Last week, I followed the 2025 New York City mayoral election and was so impressed by how clearly the New York Times visualized the election results.

In a previous post, Is Marimo the New Jupyter Notebook?

This past summer, I started using Strava as a kind of diary to record my walks and runs while on maternity leave.

When I meet other data scientists in the wild, my favorite question to ask is this: If you could get your hands on any dataset in the world, what would it be?

I've been using Jupyter notebooks for almost a decade to power everything from quick exploratory data analyses to end-to-end machine learning prototypes.

BigQuery is powerful — but it can also be expensive and slow if you don’t know what you’re doing.

DuckDB is the new kid on the (database) block and I'm not mad about it.

I use BigQuery almost every day at work and have grown to love it over the years.