We’re seeking an experienced Statistical Programmer to lead end-to-end programming using R/Python with deep CDISC SDTM/ADaM expertise.
Key Responsibilities
- Develop, validate, and maintain analysis datasets (ADaM) and SDTM mappings compliant with CDISC standards and sponsor conventions.
- Build robust, reproducible R/Python pipelines for TFLs (tables, figures, listings) and exploratory analyses; automate QC and reporting.
- Author and review specifications (SDTM/ADaM define.xml metadata, ADRGs, SDRGs, programming specs).
- Implement end-to-end workflow orchestration, version control (Git), CI/CD, and package management for regulated environments.
- Perform statistical programming for inferential analyses per SAP; implement estimands where applicable.
- Conduct code reviews, dual programming, and rigorous validation per SOPs and 21 CFR Part 11 expectations.
- Support eSubmission readiness (e.g., define.xml, reviewer’s guides, data conformance checks with Pinnacle 21-like workflows).
- Mentor programmers, contribute to libraries/utilities, and improve standard programming practices.
- Interface with Biostats to translate SAP into executable code; troubleshoot data issues across EDC to SDTM/ADaM flow.
- Collaborate on data visualization and dashboards for study teams and interim looks.
Required Qualifications
- 5–8+ years in clinical/biopharma statistical programming with direct ownership of SDTM and ADaM deliverables for Phase I–III studies.
- Advanced proficiency in R and/or Python for clinical reporting:
- R: dplyr/tidyr, data.table, haven, broom, ggplot2, quarto/rmarkdown, pkg development.
- Python: pandas, numpy, statsmodels/scikit-learn (as needed), plotly/matplotlib, pyreadstat.
- Deep working knowledge of CDISC standards (SDTM, ADaM, Controlled Terminology), define.xml, ADRG/SDRG.
- Practical SAS awareness for reading/writing XPT, integrating legacy code, and interpreting SAS-based specs/logics.
- Strong Git, code review, and documentation discipline; experience with reproducible pipelines (e.g., make/targets, renv/packrat, virtualenv/poetry, containers).
- Excellent communication; ability to partner with Biostatistics and lead programming workstreams.
Education
BS/MS in Statistics, Biostatistics, Computer Science, Data Science, or related field.