Senior Data Scientist, Epidemiology & RWE Analytics

About the role

iQVIA is looking for a Senior Data Scientist in Dublin (hybrid or site-based) to design, execute and deliver rigorous, decision-relevant real-world evidence analyses while advancing a scalable, AI-enabled analytics capability. The role combines epidemiological expertise, advanced analytics and data science, working closely with the Head of Rapid Analytics and stakeholders across EpiRWE therapy areas such as Virology, Oncology and Inflammation.

Key responsibilities

• Translate evidence needs into research questions and analytical plans using OMOP and native datasets (EMR, claims, molecular data)
• Design, run, interpret and report observational and epidemiologic studies; plan statistical analyses, define cohorts, program and report results
• Apply observational methods, evaluate assumptions and biases, and develop statistical analysis plans, models and quality-control strategies
• Use R, SQL and Python, and apply GitHub version control and reproducible research practices
• Work with OMOP CDM and OHDSI to build reusable cohorts, phenotypes, concept sets and study packages, and support federated analytics
• Evaluate real-world data sources (claims, EHR, registries, lab data, patient-generated data) and extend approaches beyond OMOP when needed
• Identify automation and AI opportunities, turn needs into technical requirements and user stories, and validate automated outputs with engineers
• Build reusable templates, standards and study packages, and promote continuous improvement and governance

Required profile

• Advanced degree in Epidemiology, Biostatistics, Health Services Research, Public Health, Biomedical Informatics, Data Science or a related quantitative field
• Expertise in epidemiologic study design, statistical analysis, causal inference and bias/confounding evaluation
• Experience with healthcare claims, EHR, registry, laboratory and other real-world data sources
• Hands-on analytical programming and experience with machine learning, AI or advanced methods on real-world data
• Ability to turn scientific questions into protocols, analysis plans and technical requirements, and to explain complex findings to technical and non-technical audiences

Required skills

• R, SQL and Python
• Version control (GitHub) and reproducible workflows
• OMOP CDM and OHDSI