Biostatisticians

The University of Utah Data Coordinating Center (DCC) is seeking a biostatistician to join our collaborative, data‑driven team. The DCC partners with investigators nationwide to provide data management, project management, and statistical expertise for large-scale multicenter research studies spanning a wide range of clinical and public health topics. As a member of the team, you will contribute to study design, perform statistical analysis, and support reporting and dissemination of results across diverse research areas.

Ideal candidates bring solid knowledge of standard statistical procedures, moderate programming skills in at least one statistical language (such as SAS or R), and familiarity with relational databases and large-scale data systems. Attention to detail, the ability to critically think through complex analyses, and a collaborative approach to problem‑solving are essential in this dynamic research environment.

The Utah DCC offers a flexible, mostly remote work schedule for candidates who reside along the Wasatch Front. While most duties can be performed remotely, the employee must be available to attend essential meetings and events on campus as needed. Occasional travel may be required.

Key Responsibilities

• Develop and manage analysis datasets and associated documentation, including dataset specifications and data checks.
• Perform statistical analyses using standard methods and statistical software (e.g., SAS, R, Stata) and prepare analytic deliverables such as tables, figures, and reports for interim and final results.
• Interpret and clearly communicate results, including statistical methods, findings, and limitations to both technical and non‑technical audiences.
• Collaborate with multidisciplinary study teams, providing statistical perspective and input across all study stages (study design, enrollment, and post‑enrollment).
• Maintain quality assurance and documentation standards for all analytic work to ensure reproducibility, transparency, and compliance with Utah DCC SOPs.
• Coordinate with supervising and faculty biostatisticians to prioritize and manage competing project timelines, communicate progress, and proactively address challenges in data or design.
• Contribute to manuscripts, abstracts, and presentations, including drafting analysis sections, generating summary outputs, and assisting with methodological explanations.
• Support database and data system development, including collaboration on data structure design, data dictionary maintenance, and familiarity with relational databases (e.g., SQL, REDCap, or other clinical data management systems).
• Identify and troubleshoot statistical or data‑related issues, proposing potential solutions and escalating as appropriate.

Engage in continuous professional development, staying current on statistical methods, programming practices, and data management tools relevant to clinical and public health research.

Minimum Qualifications

• Bachelor’s (or equivalency) + 2 years of directly related work experience or a master’s (or equivalency) degree. (One year of higher education can be substituted for one year of directly related work experience.)

Job Levels

• Biostatistician I – Requires a bachelor’s (or equivalency) + 2 years of directly related work experience or a master’s (or equivalency) degree.
• Biostatistician II – Requires a bachelor’s (or equivalency) + 4 years or a master’s (or equivalency) + 2 years of directly related work experience.
• Biostatistician III – Requires a bachelor’s (or equivalency) + 6 years or a master’s (or equivalency) + 4 years of directly related work experience.

Preferences

• Experience with SQL or similar query languages and a strong understanding of relational database structures.
• Prior experience working with large, multi‑site clinical or public health datasets.
• Demonstrated ability to manage multiple priorities effectively, meet deadlines, and maintain high‑quality deliverables in a collaborative research setting.
• Advanced programming proficiency in at least one statistical software package (e.g., SAS, R, Stata), including data manipulation and analysis workflow automation.
• Familiarity with data management tools or platforms…