Biostatistician

The University of North Carolina at Chapel Hill

North Carolina, United States0–2 yrs1h agovia LinkedIn

About the Role

The Collaborative Studies Coordinating Center (CSCC) at the University of North Carolina at Chapel Hill seeks an entry-level Biostatistician to support cohort observational studies and clinical trials. This role is crucial for ensuring sponsor deliverables are met and managing ongoing statistical demands.

Key Responsibilities

  • Serve as a practicing biostatistician on cohort observational studies and/or clinical trials.
  • Apply statistical methods for data analysis.
  • Interpret and evaluate statistical results.
  • Present statistical results in written and oral forms.
  • Interact with external stakeholders, including investigators and field center personnel.
  • Collaborate with internal team members, including research staff, programmers, and other statisticians.
  • Understand and protect the confidentiality of study data.

Requirements & Tech Stack

  • SAS software proficiency is essential.
  • MS Word, PowerPoint, Excel, and other MS Office software proficiency.
  • Experience with electronic mail software.
  • Experience with electronic informational resources.

Qualifications

  • Master’s or Bachelor’s degree with 0-2 years of experience; or a combination of related education and experience.
  • Working knowledge of applied aspects of:
  • Observational and clinical trials study design.
  • Data analysis.
  • Research data management.
  • Statistical programming.
  • Ability to meet deadlines and manage multiple assignments concurrently.
  • Ability to analyze data.
  • Effective communication skills (written and oral).
  • Good interpersonal skills.
  • Absolute accuracy and attention to detail.

Experience with applied data analysis, such as linear and log-linear modeling, survival analysis, and survey sampling, is recommended.

Experience working on complex health research projects requiring complex data management and analysis is highly desirable.

Experience with other high-level statistical software packages (such as R or M-plus) in addition to SAS is desirable but not essential.

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