Senior Scientist, Claims and Real-World Data

Job Responsibilities

• Own the design, transformation logic, and quality control of claims-derived data products, such as demographics, diagnoses, procedures, drugs, radiation, and mortality, ensuring fitness for purpose, traceability, and auditability.
• Define and document claims phenotyping, line-of-therapy, treatment-episode, and outcome derivations using standardized, versioned logic.
• Validate claims-to-molecular linkage and tokenization logic, partnering with privacy and legal teams to ensure compliant linkage and data sharing.
• Establish quality assurance and quality control frameworks and a maintained data dictionary, emphasizing proactive, reproducible validation.
• Serve as the claims subject-matter expert in technical discussions with partners and prospective customers.
• Partner with clinical and data product teams to harmonize claims with electronic medical record and pathology sources.
• Contribute to customer education, training, and documentation for real-world data.

Required Qualifications

• Advanced degree (PhD, MSc, or MPH) in epidemiology, biostatistics, health economics and outcomes research, health informatics, or a related field; or equivalent demonstrable experience.
• 5+ years working hands-on with administrative claims data (for example, medical and pharmacy claims, open and closed claims) in a real-world evidence or healthcare analytics setting.
• Demonstrated expertise building claims-derived variables, including line of therapy, treatment episodes, comorbidity indices, and outcome and mortality endpoints.
• Experience with claims-to-clinical or claims-to-molecular linkage, tokenization, and HIPAA-compliant data handling.
• Strong programming skills (SQL and Python or R) and a rigorous data quality-control discipline.
• Strong communication skills for technical discussions with partners and customers.
• Proficient in Microsoft Office Suite, specifically Word, Excel, Outlook, and general working knowledge of Internet for business use.

Preferred Qualifications

• Oncology real-world-evidence experience, and familiarity with electronic medical record and molecular diagnostics data.
• Familiarity with de-identification and expert determination, data governance, and dataset versioning.
• Experience supporting data partnerships or real-world evidence study delivery.