I'm a data-driven thinker with a passion for people, places, and the systems that connect them. I use data to understand the world—and to help shape it for the better. I bring not only technical depth, but vision, collaboration, and a drive to see ideas through. I'm always excited by opportunities where I can use these strengths to build something meaningful.
While living in Madrid between 2014 and 2016, I became obsessed with identity and history. I spent weekends visiting every pueblo between cities, reading histories, speaking with new friends and acquaintances to learn everything I could about where I was living and why the culture was the way it was. The cultural fabric I learned about and the ties to home fascinated me.
I knew that when I returned to California for graduate school, I would center my work around identity and history in the US. After two years, I submitted my thesis “Criminalized Landscape: Oakland's Historically and Socially Constructed Image of Criminality.” It is a deep technical analysis of the historical factors at play within Oakland, consisting of 200+ iterative statistical analyses. These analyses prove that a century of policy and perception led to the spatial and criminalized dynamics today. Finally, I offer solutions for a new way forward.
Even before living in Madrid, I studied abroad in Sevilla. There, I used a bikeshare system for the first time. I had always loved riding my bike back home and I fell in love with the city on dozens of the clunky, but extremely convenient bikes available at many of the street corners.
I made a promise to myself that I would one day bring this simple, yet awesome infrastructure to the SF Bay Area. In 2020, after seven years of working intermittently on the project, I was able to launch dockless ebikes to the entirety of the city of San Francisco and much of the Bay Area. Of course, I played one role, but it was an important strategic, operational, and analytical one.
I particularly like these examples because they demonstrate a number of qualities. There are of course the technical and analytical components – both required rigorous statistical and data analyses to be completed successfully. However, I like some of the other qualities they demonstrate more: vision, creativity, leadership, collaboration, determination, and execution.
I’m often asked whether I can build data pipelines, clean and transform messy datasets, design efficient SQL queries, or develop ML models—and the answer is yes, absolutely. However, I bring to the table more than just my technical skillset. I bring vision and creativity for how things can be better; leadership and collaboration for getting buy-in; determination and execution to get it across the finish line. The data is just my foundation for proving the impact and keeping it on track.
And finally, I am a baker, photographer, builder, and reader. I would rather not connect these to my professional traits, but I wouldn’t hold it against anyone if they wanted to.