Nobody wants a pipeline. They want the answer at the end of it.
I'm the bioinformatics engineer on the data and development team at the Bove Lab in UCSF's Department of Neurology(opens in a new tab). The lab studies multiple sclerosis along two lines: digital medicine, using wearables, phones, and remote assessment to see patients between clinic visits, and sex- and gender-informed neurology, looking at how hormones and reproductive exposures shape inflammation and repair. My job is the layer underneath both, turning what comes off a device or out of a chart into something a researcher can analyze.
My work starts where the data does, at an instrument in a clinic, a wearable, a phone, a database of records, and follows it until someone can actually use the result. That far end is my favorite part. The dashboard our neurologists open during a visit runs on data I supply: a Google Maps overlay of local MS resources that I helped build, and gait and assessment videos put in order so a clinician can watch how a patient's walk has changed over years. Knowing a doctor reads that with the patient sitting right there changes how carefully I treat every row. Pulling a structured measure out of thousands of narrative notes is worth doing for the same reason. It turns a question nobody could afford to ask into one a researcher can answer this quarter.
Some weeks that means a cohort nobody has assembled before, some weeks a figure for a grant due Friday. The deliverable changes constantly and what it's for never does. The domain happens to be neurology, but the problems are the ones every data team has: sources that disagree with each other, volumes that break the obvious approach, and results that still need to reproduce a year later. Running my own systems that long taught me the handoff matters as much as the build, so I write the glossary, the runbook, and the decision record. A system nobody else can operate isn't finished.
I came to software sideways. Before UCSF I spent three years as a chemist at the US Environmental Protection Agency, running aquatic toxicology studies. I barely wrote code there. What I did write was a VBA macro that killed a copy-and-paste job I had been doing by hand in Excel, and watching an afternoon of tedium collapse into a keystroke is more or less the whole reason I'm here. Then I learned to actually program at 42 Silicon Valley and never went back to the bench. Between the two fields I've co-authored 26 peer-reviewed papers, and my work has been cited over 450 times(opens in a new tab). The environmental research is still being published years after I left it.