Biostatistician I

The University of Texas at Austin; Austin (TX); On-site; USD 59,606 - 72,851; Full time

Job summary

The University of Texas at Austin is seeking a Biostatistician I to support translational cancer research by performing statistical analyses, managing clinical and molecular datasets, and contributing to computational workflows under supervision.

You will assist with study design, data integration, reproducibility, and interpretation of results for projects involving molecular, genomic, and clinical cancer datasets.

Qualifications

• Master’s Degree in Statistics, Biostatistics, or related field.
• Proficiency in at least two statistical software packages (SAS, R, Stata, or SPSS).

Responsibilities

• 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.

Skills

Analytical

Data visualization

Reproducible research

Version control (Git)

Collaboration

Attention to Detail

Problem Solving

Education

Master’s Degree in Statistics/Biostatistics or related field

Proficiency in two statistical software packages (SAS, R, Stata, SPSS)

Tools

R

Python

SAS

SQL

Job description

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).

Job Summary

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.

Responsibilities

• 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.

Knowledge, Skills, and Abilities

• 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.

Education & Experience

• 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.

Preferred Qualifications

• 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.

Salary Range

$66,229 + depending on qualifications

Legal and Employment Information

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 orientation, gender identity, gender expression, disability, religion, or veteran status in employment, educational programs and activities, and admissions.

Pay Transparency: The University of Texas at Austin will not discharge or in any other manner discriminate against employees or applicants because they have inquired about, discussed, or disclosed their own pay or the pay of another employee or applicant. However, employees who have access to the compensation information of other employees or applicants as a part of their essential job functions cannot disclose the pay of other employees or applicants to individuals who do not otherwise have access to compensation information, unless the disclosure is in response to a formal complaint or charge, in furtherance of an investigation, proceeding, hearing, or action, including an investigation conducted by the employer, or is consistent with the contractor’s legal duty to furnish information.

Employment Eligibility: Regular staff who have been employed in their current position for the last six continuous months are eligible for openings being recruited for through University‑Wide or Open Recruiting, to include both promotional opportunities and lateral transfers. Staff who are promotion/transfer eligible may apply for positions without supervisor approval.