Our client is looking for a Associate Director of Biostatistics. This individual will be responsible for directing the biostatistics activities for clinical studies for our sponsor client, including trial design, execution, analysis, and data interpretation, as well as working on SOPs and developing statistical methods sections of protocols. In addition, this person will be contributing to study level tasks from a statistics perspective, including selection of study design, selection of end points to meet research objectives, sample size, power, calculation and analyses methods.
Day to day activities will also include:
· Developing or review SAPs, TLF shell and specification, and reviewing CRF’s and other study documentations
· Performing statistical analyses, including the statistical programming for assigned studies, as well as interpreting data and providing statistical input to clinical protocols and Clinical Study Reports
· Lead both in-house and CRO activities related to statistical analysis, programming and data management
· Performing simulations to create mock analyses, including proposing new statistical methodological approaches to improve the efficiency and sensitivity of study results
· Provides effective guidance and communicates to CRO staff in the production of tables, figures, and listings
· Reviewing and validating analysis data sets, tables, figures, and listings
· Reviewing database design, CRF’s, and edit checks
· Attending FDA advisory committee meetings
· Reviewing and preparing ISS and ISE, reviewing CDISC/SDTM and DEFINE.XML
Ph.D. with 6+ plus years of experience or a Masters degree in Biostatistics with 8+ years of experience in a pharmaceutical or CRO environment,
Significant experience interacting with regulatory bodies
Experience in central nervous system indication preferred.
Experienced in NDA activities as a key contributor from a Statistics perspective
Knowledge and understanding of advanced statistical concepts and techniques, including experience in adaptive designs, longitudinal data analysis, handling missing data using pattern mixture models and sensitivity analysis.
Fluent in SAS data step programming including SAS macro
Familiarity with other packages such as nQuery Advisor, R would be highly beneficial