Biostatisticians

Job Summary

The Study Design and Biostatistics Center (SDBC) at the University of Utah is seeking a highly motivated Master’s-level biostatistician to join a team of approximately 30 biostatisticians and epidemiologists. The successful candidate will work in the Adam Bress Lab on high‑impact projects that apply cutting‑edge methods, including target trial emulation and modern causal inference, to evaluate the effectiveness, harms, and costs of antihypertensive treatments.

The lab uses randomized trials and large‑scale electronic health record (EHR) data to study outcomes such as cardiovascular disease, dementia, and cancer. Advanced causal inference methods are used to address real‑world evidence research challenges such as treatment nonadherence, confounding bias, irregular assessment times, informative censoring, and unmeasured confounding. The lab also investigates treatment effect heterogeneity and benefit‑harm tradeoffs to generate high‑quality evidence that informs clinical decision‑making and confirmatory trial design.

The candidate will contribute to all research phases: study design, data management, statistical programming, analysis, visualization, and result interpretation. Responsibilities include writing analysis plans, preparing reports and manuscripts, and explaining statistical methods and findings to diverse collaborators. The position offers collaboration with NIH‑funded investigators on comparative effectiveness, survival analysis, and causal inference research, mentorship by PhD‑level biostatisticians, and opportunities for professional development in a supportive academic environment.

Learn more about the great benefits of working for the University of Utah: benefits.utah.edu

• Clean and manage large, complex datasets; develop reproducible code pipelines, implement quality assurance checks, and maintain clear documentation.
• Write statistical analysis plans and perform sample size calculations; conduct data analyses, generate reports and graphical summaries, and contribute to presentations and publications.
• Apply foundational statistical methods, including multivariable regression, longitudinal analysis, categorical data analysis, and survival analysis.
• Conduct comparative effectiveness analysis using modern causal inference methods such as inverse probability weighting.
• Implement target trial emulation frameworks with observational data, including electronic health records.
• Write accurate, modular, well‑documented R code with emphasis on reproducibility and transparency.
• Collaborate effectively with investigators from diverse disciplines and communicate statistical results clearly to technical and non‑technical audiences.

EQUIVALENCY STATEMENT: 1 year of higher education can be substituted for 1 year of directly related work experience (Example: bachelor’s degree = 4 years of directly related work experience).

Department may hire employee at one of the following job levels:

• 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.

• Experience applying target trial emulation frameworks using observational data.
• Experience using Python for statistical programming and data science applications.
• Experience using AI‑assisted tools (e.g., ChatGPT, Git Hub Copilot) to enhance productivity and code quality.
• Strong organizational skills with ability to manage competing priorities and meet deadlines.
• Demonstrated ability to work effectively in a collaborative, interdisciplinary research team.
• Prior experience in biomedical or clinical research desirable but not required.
• At least one year of experience in a statistical consulting or statistical programming role.
• Meticulous attention to code accuracy, reproducibility, and documentation; experience with version control systems (e.g., Git) is a plus.
• Self‑motivated and committed to producing high‑quality, impactful research in a collaborative setting.

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