Biostatistician III
Job Description: Biostatistician III Location: 100% Remote Position Overview Seeking a hands-on Biostatistician III to support clinical development activities by analyzing existing Phase II clinical-trial data and generating statistical insights to inform Phase III planning. The ideal candidate will have a strong academic background in Statistics or Biostatistics, excellent SAS programming skills, practical statistical modeling expertise, and recent experience independently implementing complex statistical analyses and simulations.
Key Responsibilities
Independently implement statistical analyses using established analysis plans and project requirements. Analyze existing Phase II clinical-trial data to support upcoming Phase III study planning and design decisions. Develop, execute, validate, and maintain statistical analysis programs using SAS and/or R. Extract, manipulate, and analyze clinical-trial data from existing SDTM and ADaM datasets. Conduct statistical simulations and modeling to evaluate study design assumptions, statistical power, and Type I error rates. Apply statistical methods, including ANCOVA, multiple imputation, and multiplicity adjustment techniques, as applicable. Interpret analytical results and communicate statistical findings to internal statisticians and cross-functional stakeholders. Apply sound statistical theory and methodology to address study-related analytical questions. Incorporate reviewer feedback and make necessary adjustments to statistical programs and analytical outputs.
Required Qualifications
Master’s degree or PhD in Statistics or Biostatistics. PhD in Statistics or Biostatistics strongly preferred. Strong, recent, hands-on SAS programming experience. Demonstrated ability to independently implement statistical analyses, rather than only review or interpret results. Solid understanding of statistical theory, statistical modeling, and clinical-trial analysis principles. Practical experience developing and executing statistical programs and simulation studies. Experience working with clinical-trial data and interpreting statistical results. Ability to work independently, manage competing priorities, meet deadlines, and collaborate effectively with cross-functional teams.