Senior Data Analyst I - Real-World Evidence (Hybrid, Serbia)

About the role

Syneos Health is hiring a Senior Data Analyst I for its RWE (Real-World Evidence) team in Belgrade, on a hybrid basis. The role contributes to the design of RWE studies, leads statistical analysis plans and performs advanced statistical analyses, with client-facing support and a consulting approach.

Key responsibilities

• Contribute to the design of RWE studies, including protocol development, and lead statistical analysis plans (SAPs) and other key study documents, independently for straightforward studies such as treatment patterns or purely descriptive ones
• Apply knowledge of real-world data sources (claims, EMR/EHR, registries, omics, wearable data, PROs) to study design, feasibility and methodology
• Perform advanced statistical analyses using SAS, R, Python, SQL and other tools, ensuring data quality, reproducibility and traceability
• Develop operational definitions, code lists and analytical specifications, and prepare tables, figures and listings (TFLs)
• Contribute to study reports, manuscripts and client deliverables with clear interpretation of findings and limitations
• Support clients by presenting planning and project updates, explaining methodologies and answering technical questions
• Manage programming timelines and analytical workstreams across multiple concurrent projects, communicating progress and risks to stakeholders
• Occasionally support proposal development, desk research and exploratory analyses

Required profile

• Master's degree or higher in Biostatistics, Statistics, Epidemiology, Public Health, Health Economics, Bioinformatics, Computer Science or a related quantitative discipline, or equivalent education and experience
• At least 5 years of project-based experience conducting RWE research with secondary healthcare data sources (minimum 3 years)
• At least 5 years of hands-on statistical programming experience (minimum 2 years in a consulting setting)
• Strong understanding of RWE methodologies, observational study designs, bias and confounding control, and data governance
• Excellent written and verbal English, with client-facing experience and presentation skills
• Ability to manage multiple priorities, work independently and meet tight deadlines

Required skills

• Fluency in at least one of SAS or R (mandatory)
• Advanced statistical programming in SAS, R, Python and/or SQL