RWE Programmer

We are currently seeking a RWE Programmer to join a sponsor-dedicated team supporting a global pharmaceutical partner. This is a fully home-based opportunity. 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. Qualifications (Minimum Required) 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. Experience 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. Skills & Competencies 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. Learn more about our EEO & Accommodations request here.