Senior Statistical Analyst

JR158816 Senior Statistical Analyst

ICON plc is a world-leading healthcare intelligence and clinical research organization. We’re proud to foster an inclusive environment driving innovation and excellence, and we welcome you to join us on our mission to shape the future of clinical development.

Senior Statistical Analyst - Real World Evidence

We are currently seeking a Senior Statistical Analyst to join our Real World Evidence (RWE) team. This position offers an exciting opportunity to work on observational research studies, real-world data analyses, health outcomes research, and epidemiology projects that help generate evidence to support healthcare decision‑making.

As a Senior Statistical Analyst, you will play a key role throughout the project lifecycle, from study design and statistical planning through to analysis, reporting, publication and client interaction. The role requires strong technical expertise in SAS programming, statistical methodology, and the interpretation of complex healthcare datasets.

• Support study conception, design, and protocol development for real-world evidence and observational research projects.

• Contribute to study start-up activities, including review and development of protocols, case report forms, and statistical methodologies.

• Write statistical methods sections of study protocols and develop statistical analysis plans.

• Perform sample size and power calculations.

• Review database specifications and participate in data review activities.

• Develop table, listing and figure shells and programming specifications.

• Lead the review and validation of raw and derived variables.

• Create and maintain derived datasets using SAS programming.

• Conduct statistical analyses using appropriate methodologies, including advanced and specialized statistical techniques such as longitudinal analyses, repeated measures, survival analyses, and other complex modelling approaches.

• Develop and validate SAS programs, macros, tables, listings, figures, and project deliverables.

• Lead quality control activities throughout programming and analysis processes.

• Manage and review internal and external data transfers.

• Produce project reports, statistical outputs, visualizations, tables and graphs for client delivery.

• Contribute to manuscripts, abstracts, conference presentations and peer-reviewed publications.

• Write methods and results sections for final reports and scientific publications.

• Communicate directly with clients, investigators and cross-functional teams regarding project deliverables and statistical requirements.

• Represent Statistical Analysis in proposal development and RFP activities.

• Participate in department initiatives, process improvements, SOP development and training activities.

• Deliver internal technical presentations and contribute to knowledge sharing within the team.

• Attend departmental meetings and support broader Real World Evidence research activities.

To be successful in this role, you will possess a strong statistical and programming background, together with experience working with healthcare, clinical, observational or real‑world data.

• Master's degree or PhD in Statistics, Biostatistics, Epidemiology, Mathematics, Data Science, Public Health, or a related quantitative discipline.

• Significant experience within the pharmaceutical, biotechnology, CRO, healthcare research, or Real World Evidence environment.

• Advanced SAS programming experience is essential, including development of datasets, statistical analyses, macros, tables, listings and figures.

• Strong understanding of statistical methodologies and their practical application to healthcare and observational data.

• Experience developing Statistical Analysis Plans (SAPs) and analysis specifications.

• Knowledge of observational study design, epidemiology, health outcomes research, registries, claims databases, electronic health records, or other real-world data sources is highly desirable.

• Experience applying statistical techniques such as regression modelling, survival analysis, repeated measures analysis and other advanced methods.

• Ability to independently manage statistical deliverables while collaborating effectively within multidisciplinary teams.

• Strong written and verbal communication skills with the ability to explain complex statistical concepts to both technical and non-technical audiences.

• Preferred Experience:

• Experience with in a Real World Evidence, Health Economics & Outcomes Research (HEOR), Epidemiology, or Data Analytics team.

• Experience authoring publications, abstracts, or conference presentations.

• Proficiency in additional programming languages such as R is advantageous.

You will be part of a collaborative team delivering high-impact research that helps shape healthcare decisions and improve patient outcomes globally. This role provides the opportunity to work on diverse, scientifically rigorous projects while developing deep expertise in…