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Remote, 12-month renewable contract
Position Summary:
We are seeking a highly skilled and detail-oriented Consultant Statistician/Programmer to support Real-World Evidence (RWE) and Health Economics and Outcomes Research (HEOR) initiatives. The successful candidate will work closely with the RWE/HEOR biostatistician and will be responsible for developing, executing, and validating statistical programs using SAS and/or R to support analyses and deliverables for RWE, HEOR, and Market Access activities.
Responsibilities:
- Collaborate with HEOR and RWE biostatisticians to provide statistical programming support across various projects.
- Develop, validate, and maintain SAS and/or R programs to support statistical analyses and reporting activities for HEOR, RWE, and Market Access studies.
- Generate high-quality tables, listings, and figures based on clinical trial data and other relevant data sources.
- Perform statistical modeling and analyses as required.
- Utilize SDTM and ADaM datasets to derive analysis datasets.
- Serve as the primary programmer on assigned projects, ensuring that programming deliverables are accurate and consistent.
- Perform quality control (QC) on statistical programs and outputs as needed.
- Ensure all programming activities comply with industry standards, study protocols, and statistical analysis plans (SAPs).
- Provide input on statistical methodologies and contribute to project deliverables.
- Maintain comprehensive documentation and audit trails for all programming activities.
- Perform rigorous data quality checks to ensure accuracy, completeness, and consistency.
Education & Experience Requirements:
- Master’s degree in Statistics, Biostatistics, Mathematics, Computer Science, or a related technical discipline.
- Minimum of 4 years of experience in clinical research, preferably within the pharmaceutical or CRO industry, with exposure to Phase I–IV trials.
- Hands-on experience with CDISC SDTM and ADaM datasets.
- Proficiency in SAS and R programming is required
Additional Skills & Experience:
- Strong analytical and problem-solving skills, with the ability to manage complex studies and meet deadlines.
- Experience with statistical techniques, including longitudinal data analysis, survival analysis, and statistical modeling/simulation.
- Familiarity with observational studies, causal inference, patient-reported outcomes (PROs), and health technology assessment (HTA)
- Experience with indirect treatment comparisons (ITCs), such as matching-adjusted indirect comparison (MAIC), is a plus.
- Prior experience in a similar role within the pharmaceutical industry, preferably with a focus on small molecule pharmaceuticals.