Principal Statistical Programmer for R Development

Job Overview
The Statistical Programmer is a key contributor to the research team, playing a crucial role in analyzing and interpreting complex data sets. They are responsible for developing and implementing statistical methodologies that will enhance our study outcomes. Reporting to the team manager, the programmer must ensure data integrity and accuracy in every phase of the project. With proficiency in various programming languages and statistical tools, they collaborate closely with team members to streamline data processes and deliver insights that drive decision-making.

Responsibilities

• Develop, update or validate R packages for clinical trial analysis (SDTM, ADaM, tables, figures, listings, submission packages, data review, etc.).
• Building complex R-Shiny applications (animations, dashboards) to address clinical questions, Health Authority requirements, and decision-making.
• Generate submission ready statistical outputs using R-Markdown or similar tools
• Lead implementation in R and train other team members.
• Write or review specifications and documentation for applications
• Collaborate with clinical, statistical and data management stake holders to understand their requirements
• Identifies problems and develops global tools that increase the efficiency and capacity of the Statistical Programming group.
• Conduct statistical programming work of clinical data using R.
• Create and/or validate all safety and efficacy study output requirements (e.g. ADaM, TLFs) consistent with data definitions and specifications and relevant study documentation (e.g. protocol, SAP, aCRF)
• Collaborates with peers and statisticians to ensure the quality, accuracy and submission readiness of clinical data

Experience and Qualifications

• Strong experience in R programming and package/application development, particularly for clinical trial data including developing and validating R packages from CRO or Pharmaceutical Industry.
• Strong programming skills in R, R Shiny and R Markdown
• Proven experience in applying R and R-Shiny for the analysis and reporting of clinical trials.
• Strong skills in data visualization and data wrangling using R.
• Proficiency in using R packages for data exploration and visualization.
• Application of statistical methodology and concepts in clinical trial analysis. Experience with R-Shiny apps for data exploration.
• Advanced knowledge of industry standards including CDISC data structures as well as a solid understanding of the development and use of standard programs.
• Ability to conduct statistical programming of clinical data using R and create/validate safety and efficacy outputs (ADaM, TLFs) aligned with study documentation (protocol, SAP, aCRF).
• Exposure to clinical trial and drug development studies is highly desirable though not absolutely require for an exceptional candidate.

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 proud to be an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, status as a protected veteran, or any other status protected by applicable law. https://jobs.iqvia.com/eoe

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.