PK/PD Statistical Programmer

Role Overview

• Program, validate, and deliver NONMEM-ready PK/PD datasets based on SDTM/ADaM standards using advanced R programming skills.
• Create high-quality PK/PD datasets for both pre-lock and post-lock clinical data.
• Independently execute programming tasks of medium to high complexity with excellent accuracy and timeliness.
• Critically review data, identify inconsistencies or gaps, and propose solutions to improve dataset quality and programming efficiency.
• Perform quality control (QC) of NONMEM datasets, including those produced by external partners.
• Support preparation of deliverables for regulatory submissions following internal Pharmacometrics guidelines.
• Conduct QC of customized R packages used for pharmacometrics workflows; enhance or build automated test suites where needed.
• Liaise with cross-functional teams including Data Management, Biostatistics, Statistical Programming, and Bioanalytical groups to resolve data issues and ensure alignment.
• Adhere to relevant SOPs, working instructions, and regulatory standards; maintain inspection readiness.
• Contribute as a technical driver in the development and improvement of new PM standardization initiatives related to dataset creation and QC.

Requirements

• Bachelor’s or Master’s degree in a health, science, IT, mathematics, or related field.
• Minimum 6 years of industry experience in clinical data analysis, statistical programming, or pharmacometrics support.
• Expert-level proficiency in R for data processing, dataset creation, and QC automation.
• Hands-on experience creating NONMEM datasets, including complex data structures for PK/PD analyses.
• Strong understanding of SDTM, ADaM, and controlled terminology.
• Applied knowledge of PK/PD principles and clinical trial concepts.
• High attention to detail with strong analytical, documentation, and communication skills.
• Ability to work independently and collaboratively across global, cross-functional teams.
• Experience building or enhancing standardized workflows for NONMEM dataset creation, submission packages, and QC.
• Experience with R package testing, validation frameworks, or reproducible programming practices.
• Familiarity with pharmacometrics workflows in clinical or real-world settings.