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Principal data scientist – r&d dsdh - preclinical sciences & translational safety

Barcelona
Johnson & Johnson
Publicada el 11 abril
Descripción

Experteer Overview As a Principal Data Scientist in PSTS, you will leverage ML, data engineering, and domain knowledge to support safety evaluations and translational research. You will partner with toxicologists, PK/PD experts, and safety professionals to build AI-ready datasets and predictive models that inform dose selection and translational interpretation. You’ll develop scalable data pipelines and contribute to harmonized data models, shaping data-driven decisions across PSTS. This role offers impact on upcoming therapies within a global, fast-growing R&D data science organization. You will work in a cross-functional environment that values innovation, collaboration, and scientific rigor.Compensaciones / Beneficios
- Develop and deploy ML/AI models for safety signal detection, dose selection, PK/PD modeling, and translational insights
- Design representation-learning, predictive modeling, and multivariate analytics across in vivo and in vitro datasets and pathology information
- Collaborate with scientific SMEs to align modeling strategies with PSTS decision points
- Apply governance, versioning, and validation standards for AI/ML pipelines
- Build and maintain scalable data pipelines integrating PSTS data sources and transform data into AI-ready datasets
- Contribute to harmonized scientific data models with data engineering and ontology teams
- Interpret scientific context with toxicology, DMPK, and safety stakeholders to translate study designs into computational requirements
- Standardize terminologies, metadata, and quality checks to improve cross-study comparability
- Collaborate with PSTS experts, R&D Data Science teams, and platform architects on high-quality data solutionsResponsabilidades
- Advanced degree (MS or PhD) in a relevant field
- 3+ years of ML and/or data engineering experience on scientific or biomedical data
- Proficiency with Python and/or R, SQL, and cloud-based tooling including workflow orchestration and version control
- Experience with ML model development, evaluation, and deployment
- Experience with biological, toxicology, PK/PD, or in vivo datasetsRequisitos principales
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