Senior Scientist, Data (AI) Scientist, Translational Safety

Senior Scientist position focused on developing AI and machine learning models for drug safety prediction across discovery, preclinical, clinical, and real-world evidence stages. The role involves building predictive capabilities to identify safety biomarkers and support evidence-based decision-making throughout the R&D lifecycle.

Responsibilities

• Design, build, validate, and deploy AI/ML solutions for translational safety prediction using multimodal data
• Develop predictive models and frameworks for biomarker identification, mechanistic inference, and clinical outcome prediction
• Integrate heterogeneous datasets across discovery, preclinical, clinical, and real-world evidence domains for safety insights
• Establish scientific validation through biological plausibility assessment, model benchmarking, and explainability documentation
• Collaborate with translational scientists, toxicology, clinical safety, and knowledge engineering teams to operationalize models

Requirements

• Ph.D. in computational biology, bioinformatics, biomedical informatics, computer science, statistics, or related quantitative discipline
• 2+ years post-PhD or 3–5 years relevant industry experience applying AI/ML in life sciences
• Track record in translational science, biomarker discovery, or drug-discovery safety applications
• Expertise with multimodal data integration and high-dimensional datasets from biological domains
• Strong knowledge of machine learning, deep learning, causal inference, and foundation model approaches
• Ability to communicate complex technical methods clearly to diverse scientific and non-technical audiences