Biostatistician

Biostatistician I – Dell Medical School

Department: Department of Medicine, Division of Oncology, Austin, TX.

Position: Biostatistician I (Full-time, 40 hours per week).

Start date: July 20, 2026 (grant‑funded through August 31, 2029).

The Biostatistician I supports translational cancer research by performing statistical analyses, managing clinical and molecular datasets, and contributing to computational workflows under the supervision of senior statisticians and research faculty. The role assists with study design, data integration, reproducibility, and interpretation of results for projects involving molecular, genomic, and clinical cancer datasets.

• Develop statistical analysis plans for translational cancer research studies.
• Support sample size estimations, methodology selection, and workflow design for molecular and clinical datasets.
• Apply standard statistical techniques to multi‑omics, genomic, and clinical outcome data.
• Perform statistical analyses of cancer genomics, molecular profiling, and clinical datasets using R, Python, SAS, or similar tools.
• Validate data integrity and reproduce results with documented analytic workflows.
• Interpret analytic outputs with guidance from senior statisticians and faculty.
• Prepare statistical summaries, tables, and figures for manuscripts, grants, and reports.
• Collaborate with faculty, clinicians, and computational researchers to interpret results and refine analyses.
• Participate in study meetings and contribute to data‑driven decision‑making.
• Support protocol development and data requests, integrating molecular and clinical datasets.
• Maintain, clean, and curate research databases containing molecular, genomic, and clinical data.
• Create reproducible workflows and basic data visualizations.
• Integrate datasets from public domain sources, institutional repositories, and structured internal pipelines.
• Document all data preparation steps to ensure scientific rigor.
• Follow HIPAA, IRB protocols, and institutional guidelines for human subjects research and genomic data handling.
• Ensure secure, ethical management of patient‑derived molecular data.
• Participate in audits or compliance reviews when required.
• Develop tables, figures, and code‑generated outputs for manuscripts, presentations, progress reports, and grant applications.
• Support drafting of statistical or computational methods sections.
• Adhere to internal controls, reporting structure, and departmental requirements.

• Analytical:
  Able to analyze large, complex genomic, molecular, and clinical datasets and derive meaningful insights.
• Technical:
  Proficient in R, Python, SAS, SQL or comparable tools; familiar with data visualization, reproducible research practices, and version control (e.g., Git).
• Collaboration:
  
  Works effectively with interdisciplinary scientific and clinical teams.
• Attention to Detail:
  Ensures accuracy and reproducibility in data processing, statistical modeling, and documentation.
• Problem Solving:
  Identifies statistical challenges, recommends solutions, and contributes to refinement of analytic workflows.

• Master’s Degree in Statistics, Biostatistics, or a closely related field; or equivalent combination of education and experience with major coursework in statistics.
• Proficiency in at least two statistical software packages such as SAS, R, Stata, or SPSS.

• Experience with clinical, molecular, or genomic data analysis in a biomedical research environment.
• Familiarity with cancer research, translational pipelines, or multi‑omics analysis.
• Experience developing analytic workflows, supporting manuscripts, or contributing to grant submissions.

$66,229 + depending on qualifications

Equal Opportunity

Employer:

The University of Texas at Austin, as an equal opportunity/affirmative action employer, complies with all applicable federal and state laws regarding nondiscrimination and affirmative action. The University is committed to a policy of equal opportunity for all persons and does not discriminate on the basis of race, color, national origin, age, marital status, sex, sexual…