Summary
Joseph Burling is a Data Quality Engineer with 11 years of experience blending data engineering, project management, and cognitive neuroscience research to build reliable, reproducible data workflows for large-scale science and healthcare. He has led cross-functional teams to deploy automated pipelines, orchestration, and infrastructure (AWS, Prefect, Terraform, GitHub Actions) and now focuses on claims data quality at UTHealth Houston. Joseph’s background as a neuroscientist and instructor uniquely equips him to translate complex experimental designs into rigorous data management and statistical modeling practices, including custom Bayesian and Stan-based solutions. He has shipped production-ready tooling for pipeline automation, data retrieval, and documentation standards, and previously developed vision and eye-tracking analysis software in C++/OpenCV for behavioral research. Known for mentoring teams and improving data curation practices, he combines domain expertise in human attention with practical engineering to speed discovery while maintaining integrity. Based in Houston, he brings a research-first perspective to applied data quality challenges that often reveals hidden biases and temporal misalignments in multi-stream datasets.
11 years of coding experience
6 years of employment as a software developer
Doctor of Philosophy - PhD, Neuroscience, Doctor of Philosophy - PhD, Neuroscience at University of Houston
Visiting Scholar, Informatics, Visiting Scholar, Informatics at Kyoto University