About

I’ve been working in newsrooms since 2016, albeit always primarily in the role of data reporting—specifically ETL, but sometimes visualization as well. Before that, I worked for Simple as a data engineer, and at Periscopic as an analyst focusing on visualization. I was still new to programming professionally then, but I still learned essential principles of data governance and communication.

I picked up R and Python for practical reasons: I was running experiments in undergrad that produced enormous datasets. In the image below, you’ll see an EEG cap with 96 electrodes, each of which took 1000 samples a second. Even over the course of the few minutes my experiment ran, the data added up quickly.

I’d been advised to work in a neuroscience lab before applying to graduate school, and not just for the sake of having it on my CV: I was told I ought to know whether I actually want to commit to 5+ years of it before I do.

I worked in a great lab with a lovely PI, but I saw how much I’d romanticized the work, underestimating how much of it was scrambling for grants and publications. I believe the incentives in professional science undermine the spirit and even the quality of work in favor of publishing an unsustainable rate of novel findings.

Outside of work and studies, I most love being outside with a field guide (or two, or three) or being anywhere with a book (or two, or three).