RCI-ABBV-35705 Clinical Statistician / Biostatistician (PhD/SAS/R Programming) (Pharma/Biotech)

Position Title: Biostatistician III Length of Initial Contract: 3 months These roles are 100% remote Position Summary Seeking a hands-on Biostatistician who can independently perform statistical analyses, develop statistical programs, work with clinical datasets, and apply statistical theory to complex analysis requirements. This is not primarily a statistical programming, validation, or review position. The candidate will be expected to personally develop programs and independently execute statistical analyses. The ideal candidate combines strong statistical methodology and theory with practical programming skills, particularly SAS. Candidates should be comfortable working independently on assigned tasks while collaborating with internal statisticians who will review the work and provide guidance when needed. Manager’s Update Independently implement statistical analyses based on established analysis plans. Develop statistical programs using SAS and, preferably, R. Work directly with SDTM and ADaM datasets to identify and extract required clinical information. Analyze existing Phase II clinical trial data to support Phase III planning and project needs. Perform statistical modeling and apply appropriate statistical methodologies. Develop and execute statistical simulations. Apply statistical concepts related to Type I error, statistical power, and multiplicity control. Perform or support analyses involving multiple imputation. Independently investigate datasets and determine the appropriate information needed to answer project questions. Follow established statistical analysis plans and independently complete assigned deliverables. Collaborate with internal statisticians and incorporate review feedback into final analyses. Complete assigned work within project timelines and deadlines. PhD in Biostatistics or Statistics is preferred. Master's degree in Biostatistics or Statistics may be considered when supported by strong relevant hands-on experience. Candidates who have moved into management/leadership and no longer perform hands-on statistical programming or analysis will not work Senior candidates can be considered if they are recently and actively hands-on. Must-Have Skills Strong SAS programming skills — this is the most important programming requirement. Strong foundation in biostatistics/statistics and statistical theory. Demonstrated ability to independently perform statistical analyses. Ability to independently develop statistical programs, rather than only review or validate programming completed by others. Experience with statistical modeling and methodologies such as ANCOVA. Hands-on experience with statistical simulations. Ability to work with SDTM and ADaM datasets. Understanding of clinical trial data and statistical analysis. Ability to independently follow an analysis plan and execute the required statistical work. Strong analytical and problem-solving skills. Ability to work independently while collaborating effectively with a broader statistical team. Required Experience Hands-on experience as a Biostatistician/Statistician, rather than solely as a statistical programmer. Recent experience independently performing statistical analyses and programming. Experience working with SAS in a statistical/clinical development environment. Experience working with SDTM and ADaM datasets is strongly expected for the strongest candidates. Experience developing and implementing statistical analyses. Experience with statistical simulations. Experience applying statistical theory to real-world analysis problems. Candidates do not need to have designed clinical trials from the protocol-development stage. Protocol development experience is not required. NDA/BLA ownership or primary statistician experience is not required. Experience implementing an existing Statistical Analysis Plan is acceptable and relevant. There is no fixed maximum number of years of experience; the key consideration is whether the candidate remains sufficiently hands-on. Preferred Skills Experience with both SAS and R; however, strong SAS experience is more important. Experience with multiple imputation. Experience with multiplicity control. Understanding and practical application of Type I error and power calculations. Experience using simulations for multiplicity, Type I error, or power-related assessments. Strong experience working with ADaM and SDTM datasets. Pharmaceutical, biotechnology, CRO, or clinical research experience. Experience supporting Phase II and/or Phase III clinical programs. Experience independently implementing statistical analyses from an established analysis plan. Recent hands-on clinical statistical programming experience. Education : Master or PhD in Statistics or Biostatistics (PhD preferred) Job requirement: Proficiency in R, SAS, and/or Python, with demonstrated expertise in developing, validating, and implementing statistical analyses and simulation studies, such as ANCOVA, multiple imputation (MI), multiplicity control (type I error control, power calculation). Solid understanding of statistical theory and hands-on experience with statistical computing, simulations, and data interpretation Ability to independently lead statistical activities and also work in a collaborative environment. Responsible for overseeing all aspects of statistical planning and analyses for clinical programs; directs both internal and external SAS programming efforts related to the responsible clinical programs. MA or Ph.D. in (Bio)statistics. Requires 5 to 7 years of experience in pharmaceutical or biotechnology industry. Must have experience preparing analysis programs for clinical trials phases I-III. Must have been primary statistician on at least one NDA/BLA. Must have sound knowledge of statistical applications for clinical trials. Excellent writing and communication skills, and knowledge and skills of programming important. Strong knowledge of and experience in clinical trials design. Very good knowledge of drug development regulations pertinent to trial design and statistical analysis.