Senior Consultant, Real-World Evidence (RWE) & HEOR

About the role

IQVIA is expanding its RWE/HEOR team in Korea, with a growing focus on real-world data in post-marketing evidence generation, risk management planning (RMP) and regulatory decision-making, as well as multi-source real-world data networks and research ecosystems. Experience in either area is welcomed but not required.

Key responsibilities

• Carry out HEOR work such as database studies, longitudinal retrospective and prospective observational studies, cross-sectional surveys of patients, healthcare providers and payers, and patient-reported outcomes research.
• Develop, review, implement and execute outcomes research protocols, statistical analysis plans and reports, working independently or within a project team under supervision.
• Sourcing and collecting local data, developing analysis plans and contributing to complex health economic models.
• Take part in business development and internal initiatives, including partial proposal development from client RFPs, knowledge sharing and presentations to IQVIA colleagues.
• Manage projects, liaise with clients, attend meetings and present research findings.
• Draft, revise, submit and present abstracts, posters and manuscripts for publication and conferences.
• Contribute to RWE applications in post-marketing evidence generation, including RMP, safety evaluation, drug utilization assessment and post-authorization evaluation.
• Support multi-site RWE studies using hospital EMR data, including site onboarding, data governance, IRB/DRB strategies and standardized analytical approaches.

Required profile

• 6+ years of experience in outcomes research using real-world data sources such as claims databases and hospital EMR data.
• Masters' degree or higher in Statistics, Epidemiology, Pharmacoepidemiology, Public Health, Health/Medical Informatics or a related field, with RWD-based research experience, publications or scientific communications.
• Working knowledge of the Korean healthcare system and pharmaceutical industry.
• Demonstrable analytical, interpretative and problem-solving skills, and good English communication skills.

Required skills

• Working knowledge of at least one statistical programming language (SAS, R or Python).