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Statistical Programmer
Job in
Ann Arbor, Washtenaw County, Michigan, 48113, USA
Listed on 2026-07-24
Listing for:
A2 Ai
Full Time
position Listed on 2026-07-24
Job specializations:
-
IT/Tech
Data Analyst, Data Scientist
Job Description & How to Apply Below
- Generate and validate CDISC SDTM and ADaM datasets related to noncompartmental analysis (NCA), including PC/PP, ADPC, ADPP, and other relevant domains.
- Develop submission-ready datasets that comply with CDISC standards, implementation guides, and controlled terminology.
- Perform dataset validation using Pinnacle 21 (Community and/or Enterprise) and resolve validation findings to ensure regulatory compliance.
- Prepare and maintain Define-XML packages and supporting metadata for regulatory submissions.
- Develop and maintain programming code using R and/or SAS to create, validate, and QC clinical datasets.
- Perform quality control (QC) of datasets, programming outputs, and submission documentation to ensure accuracy, completeness, and consistency with source data.
- Support regulatory submissions to agencies such as the FDA, PMDA, and EMA by producing high-quality, submission-ready datasets and documentation.
- Bachelor’s degree in quantitative sciences, biostatistics, statistics, engineering, data science, or similar field. Master’s degree preferred.
- Experience generating and validating CDISC SDTM and ADaM NCA domains (e.g., PC/PP, ADPC, ADPP, and related datasets).
- Proficiency with Pinnacle 21 (Community and/or Enterprise) for validation.
- Proficiency with R or SAS.
- Experience preparing or reviewing Define-XML (define packages) for regulatory submissions.
- Strong understanding of CDISC standards, controlled terminology, and implementation guides.
- Experience supporting regulatory submissions (FDA, PMDA, or EMA) is preferred.
- Strong attention to detail and ability to work independently in a collaborative environment.
- This position is ideal for someone with hands-on experience in clinical data standards who can efficiently produce submission-ready datasets and associated documentation for NCA analyses.
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