I work as a senior data scientist at Lander Analytics and as an assistant research scientist at New York University (NYU). At Lander, I work on forecasting, spatial analytics, and visualizations projects; I host workshops; and consult on Posit enterprise products. At NYU, I primarily work on thinkCausal, a PRIISM project designed to make machine learning methods for causal inference more accessible. The project implements Bayesian Additive Regression Trees in a scaffolded manner for applied researchers. I graduated from NYU with a master’s in applied statistics. My advisor was Dr. Marc Scott and my continuing research is on sequence analysis.
Previously, I’ve worked under Dr. Jennifer Hill, worked at Verizon as a data scientist, and worked at J.P. Morgan as a quantitative strategist. My data scientist role primarily focused on hierarchical forecasting problems. My quantitative strategist role focused on using proprietary big data and public surveys to study the financial challenges older Americans face. I later switched roles to build a new client-facing investing platform and robo-advisor designed to serve all Americans.
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