Every path starts somewhere. This one starts here.
I’ve been working with data for over five years. In that time, I’ve built models, designed experiments, led teams, and made decisions with incomplete information — which, if you think about it, is just what data work looks like in practice. Not clean. Not certain. But deeply interesting.
For a long time, I kept most of that to myself. Notes scattered across notebooks, ideas that never made it out of my head, lessons learned from projects that didn’t go as planned. At some point, I realized that keeping things to myself wasn’t just a missed opportunity to share — it was also a missed opportunity to think more clearly.
Writing forces you to organize what you know. And publishing forces you to be honest about what you don’t.
So here we are.
What you’ll find here
This blog is where I think out loud about the things I care most about in data:
- Causal Inference — understanding not just what happened, but why. It’s one of the most underrated topics in data science, and I plan to spend a lot of time here.
- Machine Learning — from theory to the messy reality of putting models in production.
- Projects and experiments — things I’m building to learn, including what worked and what didn’t.
- Teams — because data work is rarely done alone, and the human side matters just as much as the technical side.
Some posts will be technical. Others will be more reflective. Most will probably be somewhere in between.
Why “The Uncertain Path”?
Because uncertainty isn’t a problem to be solved — it’s the environment we work in. Every model has variance. Every decision is made with incomplete data. Every career takes turns you didn’t plan for.
I’ve spent years learning to be comfortable with that. This blog is part of that process.
Thanks for being here at the start. I hope you stick around.
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