RWE Programmer

As a RWE Programmer, you will serve as a subject matter expert in Real World Data analytics and support the analysis of large healthcare databases to generate high-quality RWE for current and future compounds.

Working closely with RWE Scientists, Epidemiologists, Statisticians, and cross-functional stakeholders, you will contribute to study design, analytical strategy, database evaluation, programming, and interpretation of study results. This is a highly visible global role that combines advanced programming expertise with strong epidemiological and analytical knowledge.

Summary Of Responsibilities

• Supports Statistical programming activities in Real World Evidence.
• Provides input on study design and analysis plans where necessary.
• Develops, validates, maintains, and documents analysis programs and other study documents.
• Provides input on interpretation of results and reviews publications
• Evaluates the quality of the database.
• Provides technical database expertise to stakeholders
• Ensures that statistical outputs are produced in an efficient manner.
• Reviews the study concept, protocol design, analysis plans and other study-related documents.

• Bachelor’s degree, preferably in mathematics, statistics, computing, life science, health science, or related subjects.
• Experience and/or education plus relevant work experience, equating to a Bachelor’s degree.
• Fortrea may consider relevant and equivalent experience in lieu of educational requirements., * Typically 3-5 years of experience in Real World Evidence, Epidemiology, Health Outcomes Research, or related environments.
• Experience working with large healthcare databases such as Komodo, Marketscan, CPRD or MMIT)
• Experience in SAS or R programming within the pharmaceutical, biotechnology, CRO, healthcare analytics, or related industry.
• Python programming., * Strong understanding of Real World Evidence, epidemiology, and observational research methodologies.
• Knowledge of statistical and epidemiological analysis methods; experience with propensity score matching is a plus.
• Experience with Azure Databricks, PySpark, sparklyr, or other cloud-based analytics platforms is advantageous.
• Strong analytical, problem-solving, and data interpretation skills.
• Ability to communicate effectively with technical and non-technical stakeholders in a global environment.
• Strong organizational skills with the ability to manage multiple priorities and work independently.