The same job, five different costumes

Every environment I’ve worked in has had the same shape: important data living in messy systems, critical processes running on manual effort, and smart people separated from the answers they need by a technical gap nobody owns. My job — whatever the title said — has been to own that gap.

It started with 9-1-1 database work, where I learned what data accuracy actually means: not a quality metric, but whether help arrives at the right address. Clinical research added the discipline of protocol — data collected, validated, and documented so that someone else can trust it without trusting you. Those two experiences set a standard for data work that has never felt optional since.

At Kareo and then Tebra, I moved to the systems side of healthcare technology: leading data services, then running the reporting and operations layer for a customer success organization — Snowflake SQL, Salesforce, Gainsight, Jira Service Desk, and the unglamorous truth that most reporting problems are process problems wearing a costume. Working in a regulated, HIPAA-aware environment taught me to treat data handling as an ethical practice, not a compliance checkbox.

Higher education is where all of it converged. At Coastline College I built retention models, scraped public program requirements to find students already eligible for certificates, and ran compliance data workflows. At Orange Coast College, as a Senior Research Analyst, I automate institutional processes, build dashboards leadership actually uses, and translate methodology into decisions. The Equity Gap Calculator — a live public tool implementing the state’s disproportionate-impact methodology — is that whole career in miniature: statistics, product thinking, and translation, shipped.

The common thread is not an industry or a stack. It’s a habit: find the thing that is manual, ambiguous, or quietly broken; understand why it’s really like that; and replace it with a system people can rely on. I use modern tools to do it — including AI coding tools, used deliberately and reviewed carefully — but the value has never been the tool. It’s knowing what to build, proving it’s right, and getting people to use it.