I am currently a Senior Data Analyst for Philanthropy at Fred Hutch on the administrative side. Part of my work so far has been to assess the feasibility, accuracy and cost/benefit of predictive models for selecting donors from a prospect pool. As part of this work, I have used feature engineering to select those attributes that lead to successful identification of prospects with a minimal false positive and false negative rate and I have evaluated clustering and classification models as part of the typical data science suite of tools. I received my data science certificate from the University of Washington.
Prior to my current role, I worked for the Department of Energy (BPA) to advance the integration of renewables into their generation portfolio. This involved project management, operations research and software development. I designed an algorithm for meteorological pattern recognition to increase early warning of severe wind events in the Pacific Northwest region; I also wrote code to automate error detection in financial transactions. Lastly, I worked with senior developers in IT on algorithm design for the allocation of renewable energy credits (RECs).
I received a BA in physics from Whitman College and an MS in physics from Oregon State University. My graduate research focused on quantum (nonlinear) optics, specifically optimizing second harmonic generation in photonic crystals for peak efficiency and photon entanglement. As an undergraduate I had the privilege of receiving a research internship from the Space Grant Consortium and worked at NASA’s JPL campus. My work focused on finding empirical relationships for the probability of circuit board failure due to electrostatic discharge during deep space missions.
In my free time I enjoy reading classic science fiction, keeping current on Mayan archaeology and traveling with my wife and toddler.