RWE Analyst
Remote
Job Id:
161220
Job Category:
Job Location:
Remote
Security Clearance:
No Clearance
Business Unit:
Piper Companies
Division:
Piper Clinical Solutions
Position Owner:
Madalyn Barry
Piper Companies is seeking an RWE Analyst to support a major pharmaceutical research organization in a fully remote capacity on a contract through December 31st, 2026 based out of EST. The RWE Analyst will contribute to real‑world data initiatives within the lupus therapeutic area and assist in the development of evidence materials to support key clinical assets.
Responsibilities of the RWE Analyst include:
· Support RWE project execution in moderate‑to‑severe lupus populations, contributing to study plans and documentation.
· Draft study‑related materials, including methodological summaries, study transcripts, and project‑support documents.
· Conduct real‑world data assessment using claims and EHR databases relevant to autoimmune conditions.
· Collaborate with the existing RWE team to support asset‑related research objectives and analytical preparations.
· Assist with the development and refinement of tools and frameworks that inform study execution and evidence generation.
Qualifications for the RWE Analyst include:
· Master’s degree in epidemiology or a closely related discipline.
· Strong methodological foundation, ideally suited for early‑career researchers seeking experience in pharmaceutical evidence work.
· Hands‑on familiarity with claims and EHR data sources, including large‑scale healthcare datasets.
· Ability to produce clear, structured study documentation aligned with project goals.
· Ability to work East Coast US hours to maintain overlap with global research partners.
Compensation for the RWE Analyst:
Salary Range: $95,000-$115,000/year
Comprehensive Benefits: Medical, Dental, Vision, sick leave if required by law, and 401K
This job opens for applications on 2/26/26. Applications for this job will be accepted for at least 30 days from the posting date.
Keywords: RWE, real‑world data, lupus, SLE, epidemiology, healthcare databases, evidence generation, autoimmune research, observational methods, EHR data, claims data, study support
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