From proofs to pipelines

Two degrees, one habit of mind

I studied mathematics and philosophy at Northern Michigan University. They’re the same discipline pointed in different directions: each hands you a hard question and demands you show your work. I presented papers on epistemic logic and permutation groups, founded the Philosophy Club, and won an award for improving how the campus learned. The habit stuck: take something ambiguous, make it rigorous, make it useful.

The textbook becomes software

I spent my first decade where math meets students — at Houghton Mifflin while finishing my degrees, then in digital R&D, then four years at Pearson managing the lifecycle of more than 500 digital products: interactive books, test generators, video games, assessment systems. The textbook was becoming software, and I had a front-row seat.

In the middle of all this, I spent a year as the one-man technology department at a Chicago startup called Uncommon — servers, networks, fulfillment architecture, and campaigns with major consumer-tech, photo, and gaming brands. A startup teaches you that every problem is your problem. I never unlearned that.

The data turn

At McGraw-Hill I crossed from making products to deciding which products got made, owning a platform roadmap of 556 courses across 79 disciplines. I learned that the fastest way to win a roadmap argument is to bring data: a sales-activity analysis I piloted helped one team grow revenue 43% year over year. The thread kept pulling. At Area9 Lyceum I built a team of 23 learning engineers who shipped more than a hundred adaptive courses for healthcare, airline, pharmaceutical, and public-sector clients.

Then ETS handed me the problems I’d been training for. I built fraud analytics that rank suspicious behavior by risk and confidence, turning test integrity from reactive to proactive. I wrote a facial-detection system in Python that sharply cut security costs. And I established the ETS Center of Intelligence — data governance, self-service analytics, fourteen automated workflows — so the whole business could see itself clearly. Somewhere in there the throughline became obvious: I don’t just like analyzing things. I like building systems that make analysis unavoidable.

Strategy, at scale

Alteryx brought me inside the data industry itself. I built industry and line-of-business solution blueprints used with Fortune 500 companies worldwide, stood up the content platform that delivered them, and later became RevOps business partner to an organization of about 500 people — planning, KPIs, operating rhythms. I put GenAI into production early: an OpenAI-powered pipeline that turned scattered customer anecdotes into a searchable library of use cases. The company named me Operational Leader of the Year.

Today I lead strategy and operations for Solution Engineering at Snowflake, partnering with the Field CTO organization across AI/ML, Data Engineering, and Apps & Collaboration. Bigger stage, same job: take ambiguity, apply rigor, hand back clarity.

Off the clock

The building doesn’t stop at five. I’ve shipped iOS apps, built websites for a historical society, a poetry foundation, and an artist, and served four years on a school board — passing on the love of learning that started this story to my kids. Somewhere in Lansdale, PA, there is always a dataset open and a side project in progress. That feels right.