Overview

You will empower real world evidence studies by designing analyses, programming in SAS and R, and delivering statistical outputs that support decision-making. In the BMW Real World Evidence team, you collaborate across biostatistics, medical writing, and stakeholders to shape study design, analysis plans, and scientific communications. You will contribute to proposals, publications, and departmental initiatives while upholding ICON’s quality standards. This role offers the chance to impact healthcare research at scale and advance methodological rigor.

Compensaciones / Incentivos

- Competitive base salary
- Performance-related incentives
- Health and wellbeing programmes including medical, dental, and vision coverage
- Retirement and pension plans
- Life assurance and disability coverage
- Employee assistance programmes and wellbeing resources

Responsabilidades

- Contribute to study conception and design
- Support proposal development for full-service and statistics-only projects
- Perform SAS and R statistical analyses
- Develop and maintain SAS data manipulation and analysis programs
- Create variables, merges and analytical datasets
- Apply appropriate statistical procedures to meet project objectives
- Produce outputs such as tables,



graphs and reports
- Support scientific communications including conferences and publications
- Attend team meetings and contribute to departmental initiatives
- Assist with budgeting and scope development under oversight
- Travel domestically and internationally as needed (~5%)

Requisitos principales

- Strong SAS programming skills (data step, conditional logic, merges, ODS, procedures)
- Proficiency in R
- Experience with healthcare or research data
- Ability to develop statistical outputs, tables and graphs
- Excellent analytical, organizational and problem-solving abilities
- Effective written and verbal communication
- Ability to work collaboratively in a team
- Experience with advanced SAS techniques (repeated measures, survival analysis, SAS/Graph, macros)
- Degree in Statistics, Biostatistics, Epidemiology, Health Economics, Mathematics, Public Health or related quantitative discipline

- Collaboration
- Communication
- Problem-solving
- SAS programming (data step, Merges, ODS, procedures, macros)
- R programming
- Advanced SAS techniques (repeated measures, survival analysis, SAS/Graph)

📌 Statistical Scientist (Barcelona)
🏢 Icon Clinical
📍 Barcelona