Observational Health Data Analyst

Job Title: Observational Health Data AnalystLocation: Remote/Hybrid (no preference to remote or in person)Department: Global EpidemiologyContract: 1 year Contract with possiblity of extensionAbout the RoleThe Client's Global Epidemiology group is collaborating with a leading external data network on a major initiative focused on Lupus. We are seeking an experienced Observational Health Data Analyst to lead the analysis of diverse observational healthcare datasets. This is a high-impact role that requires a sharp analytical mind, deep understanding of real-world health data, and the technical skills to deliver high-quality insights that drive scientific and strategic decision-making.The ideal candidate is a self-starter, team player, and problem solver with a passion for working with complex, real-world data to answer meaningful health questions.Key ResponsibilitiesLead and manage the analysis of observational health data across a federated data network.Perform data characterization, data quality assessments, and recommend improvements for data quality.Develop and apply statistical methodologies and database programming techniques using R and SQL.Collaborate with European registry sites and data owners, crafting and sending detailed queries to better understand and interpret the data.Evaluate incoming site-level results for consistency and data quality; provide written recommendations for data cleaning or refinement.Use observational data to answer key research questions related to the safety, effectiveness, and potential use of drug products in the Lupus therapeutic area.Write analytic code and build visualizations using the OHDSI tool stack and relevant R packages.Contribute to internal documentation, reporting, and presentations for cross-functional stakeholders.Day-to-Day ActivitiesPartnering with data owners to review data and ensure understanding across multiple data sources (mostly registry data).Running analyses on already-standardized observational data (converted to OMOP/Common Data Model formats).Translating scientific or business questions into structured data queries and actionable insights.Engaging in regular collaboration with epidemiologists, clinicians, and data partners across Europe.Managing analysis timelines, priorities, and documentation to ensure reproducibility and transparency.Required Qualifications3–5 years of hands-on experience analyzing observational health data or working with real-world data (RWD) in healthcare.Strong proficiency in R and SQL for data analysis and statistical modeling.Demonstrated experience working with registry data and federated data networks.Familiarity with Observational Outcomes Partnership (OOP) data models or similar standard data models (e.g., OMOP CDM).Experience conducting data quality assessments, exploratory data analysis, and generating insights from complex data sets.Excellent communication skills, especially in working with external collaborators and non-technical stakeholders.Preferred QualificationsHands-on experience with OHDSI tools and R packages (e.g., Atlas, Achilles, FeatureExtraction, CohortMethod).Prior exposure to OMOP Common Data Model and associated analysis workflows.Background in epidemiology, biostatistics, health informatics, or a related quantitative health field.Experience working with messy, imperfect healthcare data – strong intuition around data cleaning, validation, and usability.