Senior Data Scientist, Epidemiology & RWE Analytics - FSP

Location: Dublin, Ireland; hybrid/site-based.

Company

IQVIA is a global provider of clinical research services, commercial insights, and healthcare intelligence for the life sciences and healthcare industries.

What you will do

• Define evidence needs with stakeholders and translate them into research questions, study designs, analytical plans, technical requirements, and delivery plans.
• Design, execute, interpret, and report observational and epidemiologic studies using OMOP, EMR, claims, molecular, registry, laboratory, linked, and patient-generated data.
• Conduct feasibility assessments, cohort definition, programming, statistical analysis planning, quality control, results interpretation, and final reporting.
• Develop reusable cohorts, phenotypes, concept sets, analytical modules, study packages, templates, standards, and quality-control frameworks for cross-database and federated analytics.
• Partner with AI, data, and software engineers to define, validate, and improve automated and AI-enabled analytical workflows while maintaining scientific oversight.
• Evaluate bias, confounding, data quality, generalizability, cross-database differences, and the reliability and traceability of analytical outputs.

Requirements

• Advanced degree in Epidemiology, Biostatistics, Health Services Research, Outcomes Research, Public Health, Biomedical Informatics, Data Science, or a related quantitative field.
• Demonstrated expertise in epidemiologic study design, statistical analysis, causal inference, and evaluation of bias and confounding.
• Experience with healthcare claims, electronic health records, registries, laboratory data, linked datasets, or other real-world data sources.
• Hands-on analytical programming experience using R, SQL, and Python.
• Experience applying machine learning, AI, or advanced analytical methods to real-world data and evidence-generation use cases.
• Experience with version control and reproducible analytical workflows.
• Ability to translate scientific questions into protocols, analysis plans, analytical specifications, technical requirements, and delivery plans.
• Strong understanding of data quality, analytical validation, quality control, traceability, and documentation.
• Ability to communicate complex analytical findings clearly to technical and non-technical stakeholders.

Culture & Benefits

• Work in a global healthcare and life sciences environment focused on improving patient care and population health.
• Access cutting-edge technology, large datasets, analytics tools, and diverse therapeutic and information technology areas.
• Opportunities for career development across geographies, capabilities, and healthcare domains.
• Inclusive and respectful workplace culture with a focus on diversity, belonging, and individual development.