This new position is needed for multiple research studies in the Department of Urology in conjunction with the UNC Lineberger Comprehensive Cancer Center. The primary purpose of this position is the management and analysis of primary health outcomes data and large secondary healthcare databases. This position will assist with the design, analysis and interpretation of diverse health services research studies, primarily using SAS and STATA. Together with UNC Urology faculty, this person will interface directly with clinical and research partners in the UNC Lineberger Comprehensive Cancer Center to help operationalize research questions, recommend and apply analytic approaches and assist with interpretation.
Education and Experience:
Demonstrated knowledge of statistical methods appropriate for analysis of health and health outcomes data. Demonstrated high level of proficiency with advanced SAS or STATA programming. Candidates with no previous SAS or STATA experience in the submitted application materials will not be considered. Ability to manage large, linked data sets (e.g., 250,000+ observations; 1000+ variables) and perform biostatistics and epidemiological methods including multivariable regression, survival analysis, longitudinal data analysis, and multi-level modeling. Good communication, collaborative/interpersonal skills, and proactive team orientation are essential. Candidates should be able to clearly document research decisions, assumptions, logic, and steps applied in study analysis.
Preferred: Experience with structural equation models, joinpoint regression, cost-effectiveness analysis, machine learning, microsimulation, and other statistical packages (e.g., R, SQL, treeage). Experience with survey data, patient-reported outcomes, or coded qualitative data.
Strongly preferred: Experience with administrative claims data (e.g., Medicare, Medicaid, Marketscan) and registry data (e.g., SEER, National Cancer Database) for cancer research. Familiarity with time-varying covariates, missing data, imputation, censoring/truncation and advanced statistical methods such as propensity score analysis, instrumental variables, Bayesian models, bootstrapping, and development/validation of predictive models.
The University of North Carolina at Chapel Hill is an equal opportunity and affirmative action employer. All qualified applicants will receive consideration for employment without regard to age, color, disability, gender, gender expression, gender identity, genetic information, national origin, race, religion, sex, sexual orientation, or status as a protected veteran.
Internal Number: 161014
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