I am the manager for the Methods branch of the Core Data Science team at Facebook, which covers a swath of research and applied work on experimental design, causal inference, identity modeling, geospatial data analysis, social measurement and statistical computing. Applications of these core methods drive impact across all manner of product, infrastructure and operational use cases at Facebook.

Prior to transitioning to management, as a data scientist at Facebook, I worked on such things as real time uncertainty quantification, statistical privacy, TMaaS (topic modeling as a service), fraud detection and survey adjustment to name a few.

Prior to prior to transitioning to management, I was in project and people management at Lawrence Livermore National Laboratory, where I served as the Applied Statistics Group Leader and project-wise was primarily focused on statistical and machine learning techniques for real time detection of network intrusions and exploits.

As for much before that, let’s just say that I could have been variably considered a Bayesian statistician, a statistical geneticist, a mathematical biologist or a passable steel drummer depending on whom you asked at UCSC, Cornell, Duke or Dartmouth. But remember now we’re getting into the pre-Facebook era so there aren’t really any reliable records of this anyway.


Statistical Computing, Bayesian Inference, Network Security, Differential Privacy, Theoretical Ecology, and Orbital Mechanics