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.

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