Job Description

Job Description:

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 modelling 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.

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.
  • 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 modelling/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.

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