Details for the position are as follows:
We are seeking a highly skilled and curious RWE Data Scientist/Analyst with expertise in statistical analysis and healthcare data to support evidence generation efforts. The ideal candidate will bridge the gap between programming and epidemiologic study design to inform business and medical decisions. You’ll work with real-world data (RWD)—such as claims, EMRs, and clinical registries—to identify care gaps, measure medical impact, and support strategic priorities across therapeutic areas.
- 2 year contract to start with the possibility of extension or conversion depending on performance and budget.
- Rate: 1-2 years $45-51 / 3-5 years $52-63 / 5-10 years $64-82
We are seeking a highly skilled and curious RWE Data Scientist/Analyst with expertise in statistical analysis and healthcare data to support evidence generation efforts. The ideal candidate will bridge the gap between programming and epidemiologic study design to inform business and medical decisions. You’ll work with real-world data (RWD)—such as claims, EMRs, and clinical registries—to identify care gaps, measure medical impact, and support strategic priorities across therapeutic areas.
- Design, plan, and execute data analysis projects using real-world healthcare data.
- Develop and apply clinical algorithms and statistical models to support study outcomes.
- Communicate analytical findings to cross-functional stakeholders in a clear and engaging way.
- Serve as a subject matter expert for RWE analytics within your assigned therapeutic area.
- Standardize code and processes to ensure analytical efficiency and scalability.
- Partner with Medical Engagement, HEOR, and other stakeholders to frame questions, align study designs, and translate business needs into actionable analyses.
- Identify appropriate data sources and collaborate with internal/external partners to drive execution.
- Lead or support the development of data dictionaries, analysis plans, and reports.
- Master’s or PhD in public health, health outcomes, statistics, or epidemiology. More than 10 years’ experience will be considered overqualified.
- Used at least two of these tools: Python, SAS, or R.
- Know how to analyze healthcare data—especially real-world data like insurance claims, electronic medical records, or clinical outcomes.
- Familiar with how clinical research studies are designed (epidemiology basics).