Senior NONMEM Programmer

About the job DescriptionSponsor-dedicated: Working fully embedded within one of our pharmaceutical clients, with support from Cytel, you'll be at the heart of our client's innovation. As a Senior Statistical Programmer, you will be dedicated to one of our global pharmaceutical clients, driving the next generation of patient treatment with autonomy and ownership. This is an exciting time to be part of this new program.

Position Overview: The position supports the PM leader or CPP leader who is the modeling lead in development and execution of PK/PD Modeling and Simulation activities related to research, design, implementation, data analysis, interpretation, reporting, and publication of CPP-sponsored and -supported studies for products in any phase of development. The role primarily focuses on data-related and e-submission-related aspects.

Responsibilities:
• Prepare programming scripts (e.g., R, SAS) to generate NONMEM analysis input dataset(s) for PK and/or PD analysis, based on requests from the PM leader or CPP leader who is the modeling lead. During dataset generation, the PM support modifies the variable definition file (PM leader or CPP leader is the main author of this document) to clearly define each variable within the dataset.
• The NONMEM input dataset(s) could be for interim or final analysis, sourced from interim (uncleaned) or final SDTM/ADAM datasets or other formats, requiring extensive data cleaning and complex calculations.
• Upon request, QC the NONMEM input dataset(s) generated by another PM support, logging the QC script used, subjects checked per study, aspects checked within the dataset, findings, and follow-up actions in a QC document.
• Generate e-submission packages for NONMEM analysis, including NONMEM input datasets, control files, output parameter files, output table files, and supporting documents such as define and var-names-descr files. PM support renames files to fit e-submission package naming conventions, converts them to appropriate formats, and places them in the correct folder structure, linking them to define and var-names-descr files. Works closely with the EPOD team to ensure the e-submission package has the right structure, correct formats, and is placed in the right assembly server directory.
• Provide guidance to new or junior members of the CPP community for the DataFlow process, including kickoff meetings to outline scope, timelines, and support needed from other departments (e.g., Data Management, Programming, Bioanalysis/Biologics Development Science). Monitor timelines during dataset preparation, answer questions from PK office vendors, and review datasets for feedback or modifications.
• Provide guidance to new or junior members of the CPP community for the Data Collection Tools review process, covering eCRF, diary (if applicable), lab requisition forms (if applicable), and completion guidelines.
• Interact with other departments (e.g., Data Management, Programming, BAN/BDS, EPOD) and external vendors (e.g., PK office vendors) to communicate CPP needs in data collection, formatting, and representation. Promote cross-departmental understanding through discussions and trainings.
• Revise, update, and create (if needed) SOPs, job aids, templates, and training materials for CPP internal and cross-departmental processes.
• Improve CPP internal processes in dataset creation, dataset QC (e.g., standard QC R script with a checklist), and e-submission package preparation (e.g., R script for automating document linking).
• Support the needs of the CPP community in setting up secure exchange mediums.

Qualifications:
• Bachelor’s degree in Statistics, Computer Science, Mathematics, etc.
• At least 6 years of SAS programming experience working with clinical trial data in the Pharmaceutical & Biotech industry with a bachelor’s degree or equivalent.
• At least 4 years of related experience with a master’s degree or above.
• Study lead experience, preferably juggling multiple projects simultaneously.
• Strong SAS data manipulation, analysis, and reporting skills.
• Solid experience implementing the latest CDISC SDTM/ADaM standards.
• Strong QC/validation skills.
• Good ad-hoc reporting skills.
• Proficiency in efficacy analysis.
• Familiarity with the drug development life cycle and experience with the manipulation, analysis, and reporting of clinical trials’ data.
• Experience with submissions utilizing define.xml and other submission documents.
• Experience supporting immunology, respiratory, or oncology studies would be a plus.
• Excellent analytical and troubleshooting skills.
• Ability to provide quality output and deliverables in adherence with challenging timelines.
• Ability to work effectively in a globally dispersed team environment with cross-cultural partners.