Senior Scientist, Data (AI) Scientist, Translational Safety (AI)

Location: Hybrid role based in Spring House, Pennsylvania, United States; also posted for Cambridge, Horsham, New Brunswick, Raritan, and Titusville, United States.

Salary: $109,000–$174,800 annually

Company

Johnson & Johnson develops healthcare, Innovative Medicine, and MedTech solutions focused on preventing, treating, and curing complex diseases.

What you will do

• Design, build, validate, and deploy AI/ML solutions for translational safety prediction across discovery, preclinical, clinical, and real-world evidence data.
• Develop predictive models and AI-reasoning frameworks for safety, biomarker identification, mechanistic inference, and clinical outcomes.
• Integrate imaging, phenomics, transcriptomics, proteomics, EHR, claims, and other heterogeneous datasets to identify biological insights and safety signals.
• Establish biological plausibility, benchmark performance, and prepare explainability and validation packages for regulatory and cross-functional review.
• Prototype foundation-model connectors and AI-enabled reasoning capabilities linking discovery, preclinical, clinical, and RWE domains.
• Collaborate with translational scientists, toxicology, clinical safety, pharmacovigilance, Knowledge Engineering, Data Products, and external partners.

Requirements

• Ph.D. preferred in computational biology, bioinformatics, biomedical informatics, computer science, statistics, applied mathematics, or a related quantitative discipline, or equivalent experience.
• At least 2 years of post-Ph.D. experience or approximately 3–5 years of relevant industry experience applying AI/ML in life sciences.
• Experience in translational science, biomarker discovery, safety assessment, or drug-discovery applications.
• Strong Python programming and experience with PyTorch or TensorFlow, deep learning, transformers, CNNs, graph networks, self-supervised learning, causal inference, and graph analytics.
• Experience with multimodal representation learning, foundation models, LLMs, GraphRAG, imaging or microscopy, multi-omics, and clinical data at scale.
• Strong analytical thinking, scientific rigor, communication, collaboration, and ability to translate domain questions into robust AI solutions.

Nice to have

• Publication record or contributions to top-tier conferences or journals.
• Experience producing regulatory-acceptable model evidence, operationalizing models in decision workflows, or building reusable model assets for R&D.

Culture & Benefits

• Inclusive work environment centered on individual dignity, diversity, and equal opportunity.
• Hybrid work arrangement within the United States.
• Retirement pension and 401(k) savings plans, subject to plan terms.
• Vacation, sick time, holidays, parental leave, caregiver leave, bereavement leave, volunteer leave, and other paid-time-off benefits.
• Interview accommodations are available for applicants with disabilities.