RWE Programmer
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Job Summary
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):
Bachelors degree preferably in mathematics statistics computing life science health science or related subjects.
Experience and/or education plus relevant work experience equating to a Bachelors degree.
Fortrea may consider relevant and equivalent experience in lieu of educational requirements.
Experience:
Typically 3-5 yearsof 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.
Required Experience:
IC
