I went looking for data science before my program offered it.

My MBA program did not offer data science, so I petitioned the dean to build my own curriculum around it. That was the start of ten-plus years building analytics ecosystems from zero and the governance layer that makes them trustworthy.

The pattern repeated. I built a division's data-science and reporting ecosystem from scratch in hi-tech manufacturing. I built a global commercial reporting ecosystem from the ground up in rare-disease pharma, then architected the enterprise data-governance framework and single source of truth that organization runs on now. Different sectors, same job: work out how the thing actually works end to end, then build the version that holds up even as leadership changes.

What I am best at is the seam between commercial strategy and data infrastructure. Sitting with marketing and sales to understand what they are actually trying to do, then making the platforms, the signals, and the taxonomy carry it. Almost none of that is solo work. It is done with platform owners, developers, IT and outside agencies, and it only holds if those people are brought along rather than handed a standard.

I care about doing this honestly: defensible numbers, named limitations, no overclaiming. The patient-finding work on this site is labeled as architected and prototyped on synthetic data because that is exactly what it is.

Away from work, the part that matters most is my family. I am a husband and a father of two, and most of my time off the clock goes to them: to baseball and the kids' sports, to fishing, and to a workshop full of 3D design and printing. That is the version of me a resume never shows.