Writing programs to clean data and perform statistical analysis in SAS, Stata, R, and/or Python.
Perform statistical analyses using a variety of statistical models and methods, including generalized linear models (e.g., linear, logistic, and count regression), survival analyses, mixed models, and machine learning techniques.
Perform cleaning and documentation of data generated from Institute studies or studies run by Institute investigators, including the Community Firearm Violence Prevention Network studies; these may include primary data, as well as data from large databases and complex survey samples.
Contribute to study design decisions, including sample size justification and analytic approach.
Documentation and presentation of analytic results.
Creating high quality data visualizations for data briefs, manuscripts, or presentations.
Procuring external data sources needed to supplement studies (e.g., publicly available data from the census, CDC WONDER, ICPSR, or other sources).
Facilitate project management for multi-investigator studies by preparing agendas and occasionally leading meetings, tracking action items, and organizing data-retreat sessions to keep deliverables on time.
Translate study protocols into REDCap survey instruments, designing questionnaire logic, branching rules, and validation checks to ensure clean, analysis-ready exports.
Operate in a data-manager capacity, continuously monitoring live survey data, troubleshooting participant or platform issues in real time, and maintaining rigorous version control across successive survey waves.
When appropriate co-author manuscripts and technical briefs by drafting Methods/Results sections and summarizing statistical findings.
If needed, provide hands-on mentorship to undergraduate research assistants on analytic workflows, science communication, and research processes.