Responsibilities Contribute to the development of a portfolio of RWE projects based on RWD that will provide key insights to our pipeline assets Leverage emerging scientific and technological developments to generate new research ideas, solutions and initiatives using real-world data End-to-end experience in RWE studies including conceptualizing the research questions, data feasibility, study design, analysis, programming, and interpretation Analyze and interpret data to support urgent requests from internal and external stakeholders Ensure quality of design, execution, and publication of real-world evidence studies, and quality of models & tools Create study protocols, statistical analysis plans, and statistical programming deliverables Clearly articulate highly technical methods and results to diverse audiences and partners to drive decision-making Ensure RWE generation aligned with regulatory requirements and scientific standards Requirements A Ph. D. degree, or master’s degree in a quantitative field (e.G., biostatistics, AI Data Science, Bioinformatics, similar) Relevant experience (2+ years for Ph. D., 4+ years for a master’s) within biopharma companies, RWE consulting firms, or other relevant healthcare industries Experience designing and executing studies using real-world healthcare data, such as claims, electronic health records (EHRs),



or registries Extensive hands‑on experience with data engineering and data analysis Proven track record of consistently delivering on high impact data science projects Expert proficiency in either R or Python, SPARQL, Cypher Excellent interpersonal, communication, and presentation skills Experience delivering on Data Science projects using predictive technologies as machine learning/deep learning, or forecasting Familiarity with and exposure to drug discovery and clinical development processes with one or more of the following therapeutic areas: oncology, immunology, neuroscience, or specialty ophthalmology Hands‑on experience with graph neural networks and related graph ML methods for learning across large, heterogeneous, multi-domain graphs. Hand‑on bioinformatics experience running and interpreting results in a biological/disease context, including pathway or functional enrichment analysis. Core Competencies Demonstrates expertise in Real-World Evidence (RWE) study design, data analysis, and programming, with a strong focus on delivering impactful data science projects in the biopharma sector. Proficient in communicating complex methodologies and results to diverse stakeholders while ensuring compliance with regulatory standards. #J-18808-Ljbffr

📌 Principal Data Scientist, Real World Evidence (Madrid)
🏢 Jobtailor
📍 Madrid