The Statistical Programming division within the Clinical Quantative Sciences department works closely with Data Management and Biostatistics to provide analyses of Clinical Trials Data in a regulated environment. The statistical programming role is a critical function that helps to further Juno's mission by making data accessible and interpretable, and facilitating rapid regulatory review and approval by providing a comprehensive and compliant study data submission package for filing.
Develop or QC SDTM and ADaM datasets
Work with Biostatistics to maintain programming related specifications and documentation.
Coordinate development of SAS code to produce tables, listing and figures used for clinical study reports, ad hoc analyses, integrated analyses and publications.
Review and provide input for study related documents, such as case report forms, database design and database edit check specifications, Statistical Analysis Plans, TFL specifications, etc.
Provide statistical programming support for multiple clinical projects
With oversight, function as leader on larger projects by coordinating the activities of multiple programmers (including CROs) and ensuring the consistency, accuracy, and timely completion of programming, validation, and documentation for those projects.
Contribute to and implement team programming standards across all studies and comply with all regulatory requirements
Develop standard macros and/or tools in SAS for data analysis and reporting
Minimum of 6 years of years progressive statistical programming experience within the biotech or pharmaceutical industry
Advanced SAS programming skills, including macro language and ODS experience.
Independent contributor with excellent communication and adaptive skills along with a high level of interpersonal collaborative/team skills to influence and build strong internal and external relationships.
Knowledge of ICH, eCTD and FDA (21 CFR Part 11, ele) guidelines
Solid foundation in CDISC SDTM and ADaM
M.S., or B.S. in biostatistics, statistics, computer science, or other relevant scientific area