Principal Data Strategist Real World Evidence

About the role: The Principal Data Strategist, Real World Evidence (RWE) will lead enterprise real-world data (RWD) strategy and advanced analytics initiatives that support scalable, regulatory-aligned evidence generation. This role combines strategic leadership in data sourcing, vendor assessment, governance, and long-term data planning with deep expertise in real-world evidence, epidemiology, and data science. This incumbent will be operating with a high degree of autonomy, this individual will shape fit-for-purpose RWD strategies, evaluate and operationalize external data assets, and lead advanced analytics initiatives using EHRs, claims, registries, and linked healthcare data. The role partners closely with Clinical, Medical Affairs, Regulatory, HEMA, IT, Biostatistics, Quality, and R&D stakeholders to advance both immediate evidence generation priorities and long-term data capabilities. Responsibilities will include: Data Strategy & Vendor Management: Support enterprise RWD strategy development and long-term data planning aligned with evidence generation priorities. Evaluate and operationalize external data assets including EHR, claims, registry, and emerging healthcare data sources. Lead vendor assessments and data source evaluations including quality, linkage feasibility, scalability, governance, and regulatory suitability. Partner cross-functionally to support data acquisition, governance, integration, and scalable analytics infrastructure. Provide strategic guidance on fit-for-purpose data selection, feasibility assessments, and analytic approaches. Study Design & Execution: Lead the design, development, and evaluation of RWE study protocols, including cohort definitions, endpoints, and analytic plans. Collaborate with KOLs and stakeholders to ensure robust analytical approaches and clinically meaningful outputs. Validate methodologies and results, ensuring transparency, reproducibility, and audit-readiness. Apply rigorous epidemiologic and statistical methods to address bias, confounding, and data limitations. Translate study findings into impactful reports and actionable insights to support evidence generation, value messaging, publications, regulatory submissions, and strategic decision-making. Ensure alignment of study design and execution with regulatory and methodological guidance. Oversee feasibility assessments, including data availability, fit-for-purpose evaluations, and study design optimization. Execute end-to-end RWE studies, from protocol development through analysis, interpretation, and dissemination of results. Advanced Analytics, Communication & Leadership: Develop advanced analytics solutions including predictive modeling, AI/ML methodologies, phenotyping, and NLP applications. Design dashboards and visualizations to communicate insights and support decision-making. Establish and promote best practices for data science, reproducible research, validation, and governance. Support publications, presentations, and regulatory-aligned scientific communications. Partner cross-functionally and mentor team members to advance organizational analytics and RWE capabilities. Required Qualifications: Minimum Bachelor’s degree or advanced degree in data science, biostatistics, epidemiology, computer science, health informatics, or a related field, or equivalent experience. Minimum of 5 years of experience with a Bachelor’s degree or 3 years with a Master’s degree in real-world evidence, healthcare analytics, data science, epidemiology, or related disciplines. Proven experience working with real-world healthcare data including electronic health records, claims, registries, and linked datasets. Demonstrated expertise in observational research methods, epidemiology, causal inference, and advanced statistical or machine learning methodologies. Proven proficiency in Python, R, SQL, and modern analytics environments. Experience evaluating external healthcare data assets and working with data vendors or strategic data partnerships. Strong communication and stakeholder management skills across technical and business audiences. Preferred Qualifications: Experience supporting regulatory-aligned evidence generation and health authority interactions. Experience leading enterprise or cross-functional data strategy initiatives. Experience with healthcare data linkage methodologies, tokenization, or distributed data environments. Experience applying AI/ML or NLP methodologies within healthcare or RWE settings. Experience working within a global or matrixed organization. #J-18808-Ljbffr Gateway Recruiting