Summary: Seeking an experienced PK/PD Statistical Programmer to produce high-quality, compliant datasets for modeling and analysis using R programming and NONMEM. Highlights: 1. Expert-level proficiency in R for data processing and QC automation 2. Hands-on experience creating complex NONMEM datasets for PK/PD analyses 3. Strong understanding of SDTM, ADaM, and PK/PD principles Madrid, Spain \| Full time \| Home\-based \| R1532189**Job available in additional locations*** We are seeking an experienced **PK/PD Statistical Programmer** with strong experience in **R programming**, **PK/PD datasets**, and **NONMEM dataset creation**. This role supports Pharmacometrics by producing high‑quality, compliant datasets for modeling and analysis, ensuring accuracy from early (unclean) through post‑lock clinical data. The ideal candidate brings deep technical expertise, strong problem‑solving skills, and a solid understanding of PK/PD principles.**Key Responsibilities** ------------------------ + 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.**Required Qualifications** --------------------------- + 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.**Preferred Skills** -------------------- + 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. IQVIA is a leading global provider of clinical research services, commercial insights and healthcare intelligence to the life sciences and healthcare industries. We create intelligent connections to accelerate the development and commercialization of innovative medical treatments to help improve patient outcomes and population health worldwide. Learn more at https://jobs.iqvia.com IQVIA is committed to integrity in our hiring process and maintains a zero tolerance policy for candidate fraud. All information and credentials submitted in your application must be truthful and complete. Any false statements, misrepresentations, or material omissions during the recruitment process will result in immediate disqualification of your application, or termination of employment if discovered later, in accordance with applicable law. We appreciate your honesty and professionalism.