shanjeeda shafi

I am a highly motivated public health epidemiologist and statistician with a Ph.D. in Statistics from the University of Newcastle, Australia. My doctoral research focused on machine learning and mixture clustering methods for molecular drug discovery, combining predictive modeling with domain-specific interpretation.

In my current role as a contract epidemiologist/statistician supporting CDC surveillance (through Goldbelt Professional), I provide technical assistance on COVID-19 and NHSN surveillance, publish weekly reports, maintain dashboard quality control, and develop SOPs and databases for public-facing reporting.

My research and analytical experience spans applied machine learning, mixture-based clustering, PCA/MCA/FAMD visualizations, and predictive model building using R (FactoMineR, ggplot2) and other statistical packages. I routinely write SAS macros, clean complex datasets, and present results to multidisciplinary teams.

Earlier roles include statistical and data-management work in biological research and maternal and neonatal health, where my analyses informed national policy. I prioritize data quality assurance, reproducible workflows, and adoption of data modernization tools such as Azure Databricks, Power BI, R, SAS, and Python to improve surveillance and decision-making.