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 / BeneficiosCompetitive base salaryPerformance-related incentivesHealth and wellbeing programmes including medical, dental, and vision coverageRetirement and pension plansLife assurance and disability coverageEmployee assistance programmes and wellbeing resources ResponsabilidadesContribute to study conception and designSupport proposal development for full-service and statistics-only projectsPerform SAS and R statistical analysesDevelop and maintain SAS data manipulation and analysis programsCreate variables,



merges and analytical datasetsApply appropriate statistical procedures to meet project objectivesProduce outputs such as tables, graphs and reportsSupport scientific communications including conferences and publicationsAttend team meetings and contribute to departmental initiativesAssist with budgeting and scope development under oversightTravel domestically and internationally as needed (~5%) Requisitos principalesStrong SAS programming skills (data step, conditional logic, merges, ODS, procedures)Proficiency in RExperience with healthcare or research dataAbility to develop statistical outputs, tables and graphsExcellent analytical, organizational and problem-solving abilitiesEffective written and verbal communicationAbility to work collaboratively in a teamExperience with advanced SAS techniques (repeated measures, survival analysis, SAS/Graph, macros)Degree in Statistics, Biostatistics, Epidemiology, Health Economics, Mathematics, Public Health or related quantitative disciplineCollaborationCommunicationProblem-solvingSAS programming (data step, Merges, ODS, procedures, macros)R programmingAdvanced SAS techniques (repeated measures, survival analysis, SAS/Graph)

📌 Statistical Scientist (Barcelona)
🏢 Jobrapido
📍 Barcelona