Sr Data Analyst I, RWE

syneoshealth; United States; Hybrid; USD 95,000 - 130,000; Full time

Job summary

Syneos Health is seeking a senior, individual-contributor on an RWE analytics team to design observational studies, lead analysis plans, and translate secondary healthcare data into decision-ready evidence.

The role blends hands-on statistical programming in SAS, R, Python, and SQL with client engagement, delivering tables, figures, and reports while guiding study feasibility and methodology.

Qualifications

• Master's degree or higher in Biostatistics, Epidemiology, or a related quantitative field.
• 3+ years of project-based RWE research using secondary healthcare data; 5 years preferred.
• 2+ years of hands-on statistical programming in a consulting environment; SAS or R mandatory.
• Strong written and verbal English communication with client-facing experience.

Responsibilities

• Design RWE studies, author SAP, and support documentation for descriptive or treatment-pattern work.
• Apply real-world data sources to guide feasibility and study methodology.
• Execute advanced analyses in SAS, R, Python, and SQL with reproducibility in mind.
• Produce tables, figures, listings, reports, and client-facing deliverables with narrative interpretation.
• Manage programming timelines across projects and assist with proposals and exploratory analyses.

Skills

Biostatistics

Observational study design

Client communication

Independent work

Education

Master's degree or higher in Biostatistics

Related quantitative discipline

Tools

SAS

R

Python

SQL

Job description

Role overview

This is a senior individual-contributor role on a Real-World Evidence (RWE) analytics team supporting biopharmaceutical clients across the drug development lifecycle. The position blends hands-on statistical programming with consultative client engagement, helping design observational studies, lead analysis plans, and translate secondary healthcare data into decision-ready evidence.

Responsibilities

• Contribute to the design of RWE studies, including protocol authoring, statistical analysis plan (SAP) development, and supporting study documentation, independently for descriptive or treatment-pattern work.
• Apply working knowledge of real-world data sources such as claims, electronic medical/health records, registries, omics, wearables, and patient-reported outcomes to guide study feasibility and methodology.
• Execute advanced statistical analyses in SAS, R, Python, and/or SQL with attention to reproducibility, traceability, and data quality.
• Build operational definitions, code lists, and analytical specifications aligned with study objectives and industry conventions.
• Produce tables, figures, listings, study reports, manuscripts, and client-facing deliverables, including clear narrative interpretation of findings and limitations.
• Manage programming timelines across concurrent projects, surface risks early, and support proposals and exploratory analyses when needed.

Requirements

• Master's degree or higher in Biostatistics, Statistics, Epidemiology, Public Health, Health Economics, Bioinformatics, Computer Science, or a related quantitative discipline, or equivalent experience with supporting evidence.
• At least three years of project-based RWE research using secondary healthcare data, with five years preferred.
• At least two years of hands-on statistical programming in a consulting environment (five years preferred), with strong fluency in SAS or R considered mandatory.
• Solid grasp of observational study design, bias and confounding control, and data governance considerations.
• Strong written and verbal communication in English, including client-facing presentation experience.
• Demonstrated ability to juggle multiple priorities, work independently, and deliver high-quality work under tight timelines.

Nice to have

• A consulting mindset with the ability to convert analytical results into strategic recommendations and proactively flag risks to clients.