Description:
We are looking for an experienced Senior Statistical Programmer to support clinical reporting, statistical programming, and regulatory submission deliverables in a fully remote environment. This role is ideal for someone with deep SAS programming expertise who also brings strong R programming skills, especially in a clinical data setting.
This person will work on production programming and verification activities related to clinical reporting, including SDTM and ADaM deliverables, statistical outputs, and submission support. The team is also placing increasing emphasis on R programming, so candidates should be comfortable working across both SAS and R.
Key Responsibilities
- Independently perform statistical programming for analysis datasets, tables, listings, and figures
- Support clinical reporting and submission deliverables
- Develop, validate, and verify SAS programs and outputs
- Perform SDTM and ADaM mapping and generate CDISC-compliant datasets
- Produce outputs for regulatory submissions, safety updates, publications, and presentations
- Translate statistical analysis plans and analytic specifications into high-quality code and outputs
- Work with cross-functional stakeholders in a collaborative clinical development environment
- Contribute to programming quality, accuracy, and timeline ownership across deliverables
Required Qualifications
- 8+ years of statistical programming experience within a pharmaceutical company, biotech, sponsor, or CRO environment
- Strong SAS programming experience, including Base SAS, Macro, and SAS/STAT
- Strong working knowledge of CDISC standards, including SDTM and ADaM
- Experience supporting clinical reporting, regulatory submissions, and statistical outputs
- Experience in a sponsor or CRO setting required
- Strong communication skills and ability to work independently in a remote setting
Preferred Qualifications
- Strong R programming experience in a clinical data environment
- Experience using R for data cleaning, analysis, and visualization
- Familiarity with common R packages such as tidyverse and survival
- Experience handling messy data, missingness, and scalable/modular code development
- Familiarity with GitHub and/or GitLab
- Experience with survival analysis, longitudinal data, and descriptive statistics
- Oncology experience is a plus
- Experience with macros, registries, epidemiology, or advanced statistical methods is a plus