I’m passionate about using the power of mathematics, statistics and data to improve people’s lives.

I spent my undergraduate years studying math at Penn State, where I was lucky to have great faculty, resources and enrichment opportunities available to me. On top of the standard undergraduate curriculum, I explored additional areas of study that caught my interest, including dynamical systems, Non-Euclidean geometries, mathematical logic (the area that originally attracted me to math) and finite field theory research. Interacting closely with faculty, participating in advanced study programs and getting my first taste of mathematical research convinced me to pursue further studies in grad school, where I went on to complete three masters programs.

During my first two graduate programs(MS & MMS), my primary areas of research were in the fields of mathematical neuroscience and stochastic disease modeling. My MS research and final project resulted in the publication of a new analysis of Ebola outbreak data. Working both individually and collectively with peers and mentors, we wrote code to simulate different disease transmission models centering around an SIR framework. These included branching processes, network configuration models, pairwise analytic models, and survival dynamical systems. Using these, we were able to generate a comparison of parameter estimation methods applied to an outbreak in the Democratic Republic of the Congo.

Contemplating what to pursue after grad school led me to data science, artificial intelligence and (ironically) my third masters program – one in applied statistics. I took this time to refine and add to my statistical repertoire, studying and implementing methods from traditional test design, to bayesian modeling, to nonparametric methods, to statistical learning and more. While in the program, I spent a summer as an intern for the Data & Analytics group at a bank and, ultimately, started full-time work there upon graduating.

Partnering with various segments of the bank, I provide AI, modeling, and analytics solutions & capabilities to support & optimize business and drive innovation. Among the types of projects I’ve delivered are synthetic control capabilities for causal inference, automated web-scraping capabilities, lots of predictive modeling (in the form of product recommendation, as an example), and fast, fuzzy text-matching capabilities for large data sets.

I’m eager to continue to apply the skills I’ve developed to problems in different industries and I look forward to gaining more hands-on experience and continuing to grow in the data sciences. I have a diverse range of interests including marketing, healthcare, banking, finance, consulting, etc. and am always happy to talk about data science, analytics, machine learning, artificial intelligence, etc., so don’t hesitate to reach out.