Turn your data from something you look at into something you run on.
Most companies collect plenty of data and still run on gut and argument. Reports describe what happened; they don't decide what to do next. Closing that gap is the job — and it's rarely a tooling problem.
I'm the senior data and AI leader who does both halves of it: get the model of your business right — what each number means, where the real decisions are made — then build the systems that act on it. The definitions are the hard part; the working system is how you know they were right.
And if you're earlier than that — standing up your first data function, or deciding which AI to trust before you commit — the same structural questions apply, asked before the pain instead of after.
- 20M+ membersData products and decision systems operated at national consumer scale.
- 20K+ merchantsBuilt and led data capabilities for a two-sided loyalty marketplace.
- 15-person teamBlended data organization built and led across data science, analytics, and engineering.
- $50M+ annual revenueProduction data and AI products owned end-to-end by my team.
What I do
I’m brought in as senior data and AI leadership — the range a Head of Data covers, scaled to what your company needs now: trusted metrics and the model beneath them; trusted AI and the evaluation to prove it; and the systems that make decisions on both. Part of the job is judgment about where ML and automation earn their cost and where they don’t. One through-line runs through every engagement: get the underlying model right first, then build.
Current build: an on-prem evaluation platform that tests LLM vendors, models, and configurations against an organization's own data — because "which model should we trust with this?" is an empirical question, not a procurement one.
Why it holds
Once the model underneath is settled and trusted, the work compounds instead of calcifying. The next thing your team builds starts from a definition it can rely on, not one it has to route around — and the self-serve dashboards and AI you actually wanted start working, because people trust the numbers they run on.
You can’t rebuild your way out of the wrong foundation.
Proof
Ready when you are.