About

I write about analytics problems that sit between code, data models, and explanation.

My background spans medicine, statistics, energy, biology, and insurance. I finished medical school in 2018, moved into data work, and stayed there because the mix of logic, communication, and practical problem-solving suited me better.

That background still shapes how I approach technical work: I care about detail, but I also care about whether a result is understandable and useful.

What I Work On

SQL patterns for real-world data problems
R for exploratory analysis and reproducible workflows
DuckDB and local-first analytical tooling
Analytics engineering ideas that improve clarity and maintainability
Communication patterns for making technical work easier to trust

What You Will Find Here

This website is where I publish working notes on analytics, business intelligence, modeling, and statistical thinking. Some posts are small and tactical. Others are longer walkthroughs meant to show the reasoning, not just the answer.

If you are new here, a good place to start is the blog archive or the projects page.

Background

My route into data was not linear. That is probably why I tend to enjoy messy edge cases, ambiguous business questions, and topics that cross domain boundaries. I like work that requires both technical execution and careful explanation.

Over time, the site has grown into a record of the problems I keep coming back to: date logic, query design, performance, modeling choices, and the small implementation details that make analytical work either pleasant or fragile.

Elsewhere

Now

Right now, the site is centered on writing that is practical, technical, and reusable. I want the posts here to be the kind of thing worth sending to a colleague because they save time or make an idea click.