Statistician

Job Details

Department: Lineberger Compr Cancer Center-426801

Career Area: Research Professionals

Posting Open Date: 06/12/2026

Application Deadline: 06/25/2026

Open Until Filled: No

Position Type: Permanent Staff (EHRA NF)

Working Title: Statistician

Appointment Type: EHRA Non-Faculty

Position Number: 20076715

Vacancy ID: NF0009816

Full Time/Part Time: Full-Time Permanent

FTE: 1

Hours per week: 40

Position Location: North Carolina, US

Hiring Range: Dependent upon Experience and/or Qualifications

Proposed Start Date: 07/20/2026

Be a Tar Heel!

A global higher education leader in innovative teaching, research and public service, the University of North Carolina at Chapel Hill consistently ranks as one of the nation’s top public universities. Known for its beautiful campus, world-class medical care, commitment to the arts and top athletic programs, Carolina is an ideal place to teach, work and learn.

Primary Purpose of Organizational Unit

Our mission is to improve the health and well-being of North Carolinians and others whom we serve. We accomplish this by providing leadership and excellence in the interrelated areas of patient care, education and research.

Position Summary

Lineberger Comprehensive Cancer Center is seeking a statistician with strong SAS programming and data management expertise to support multiple local and national epidemiologic studies. The position will play a key role in the design, implementation, and analysis of population-based research, including the Benign Breast Disease (BBD) arm of the Carolina Breast Cancer Study a large national effort to understand BBD and its implications as well as additional North Carolina cancer outcome cohorts.

The statistician will be responsible for overseeing study data systems; developing and maintaining high-quality analytic datasets; implementing rigorous data quality assurance procedures; and providing statistical programming, descriptive analyses, and methodological support to study investigators. Advanced SAS programming proficiency, strong statistical reasoning, efficient data management practices, outstanding documentation skills, and the ability to work independently are essential for success in this role.

Minimum Education and Experience Requirements

Master’s or Bachelor’s and 0-2 years’ experience; or will accept a combination of related education and experience in substitution.

Required Qualifications, Competencies, and Experience

This position requires substantial SAS programming and data management experience working with large, complex datasets. Candidates must demonstrate advanced proficiency in SAS data step programming, SAS macros, PROC SQL, and the generation and interpretation of descriptive statistics. Required skills include the ability to import, clean, merge, and document multifaceted data files; implement and monitor rigorous data quality control procedures; construct and document complex analytic datasets derived from multiple primary sources; and create well-defined derived variables to support statistical analyses. Experience producing descriptive summary outputs, generating formatted analytic reports, and maintaining standardized, reproducible data documentation is essential.

The candidate must demonstrate strong statistical reasoning, exceptional attention to detail, and excellent interpersonal, listening, oral, and written communication skills. Knowledge of data security principles and experience working with Protected Health Information (PHI) are required.

The ideal candidate will be able to work independently, manage and prioritize multiple tasks to meet project deadlines, and proactively acquire new statistical programming skills (in SAS or other languages) as needed to support evolving analytic needs.

Preferred Qualifications, Competencies, and Experience

Highly valued qualifications include experience conducting statistical analyses using fundamental and intermediate methods (e.g., logistic regression and other generalized linear models), as well as familiarity with modern data visualization techniques for exploratory and analytic reporting. Proficiency with additional statistical or data-centric software such as R, Python, and/or REDCap is strongly preferred.

Candidates with a PhD in biostatistics, statistics, epidemiology, or a related quantitative field are encouraged to apply and may have opportunities to contribute more broadly to analytic strategy, methodological development, and interpretation of study findings. Previous experience in biomedical or public health research is desirable but not required.