Daniel Brannock

Daniel Brannock is a research data scientist who applies analytics to health care data, particularly real-world data and electronic health records (EHRs), and criminal justice, supporting the United States Postal Inspection Service to study mail fraud victimization.  

Currently, as a part of the National Institutes of Health (NIH)-funded RECOVER Initiative: Researching COVID to Enhance Recovery, he is using EHRs from tens of millions of patients available in the National COVID Cohort Collaborative to characterize and search for treatments for Long COVID. In addition, Daniel is developing training materials that outline how to apply data science and analysis to data from the NIH’s All of Us Research Program, which is seeking to democratize access to EHRs. Outside of working on research projects with support from federal partners, he has helped a Nigerian non-governmental organization use national EHRs to build and deploy models to aid clinicians in treating HIV. Daniel is also the lead developer for RTI Fovea, a proprietary software package for finding and visualizing conditional multi-variate outliers.

Before joining RTI, Daniel was a senior data scientist at Elder Research, where he built analytic solutions across many industries while using a broad array of methodologies—from predictive machine learning models to large-scale supply forecasts.