I’m a data scientist, working in both R and Python, on problems in machine learning and computational statistics. I currently work in the health care field as a senior data scientist at Elsevier in the Precision Medicine department. I am also an organizer for RLadies, a global network of meetup groups to support gender diversity in the R community. My background is in statistical ecology where I developed basic theory and statistical tools for population and community ecologists, also known as “Data Science for Bugs.”
I’m fascinated by the ways variability or noise changes the patterns that we expect to emerge in data. I focus on computational approaches for both frequentist and Bayesian frameworks to account for variability in mechanistic models as well as machine learning techniques to train predictive models.
I live with two rescue pups, Maggie and Ruthie, who I think are really bears just pretending to be dogs. I spend most of my free time drinking coffee, hiking with the doggos, and watching baseball.
PhD in Statistical Ecology, 2012
University of California, Berkeley
BSc in Biology / Mathematics, 2005