Lead Data Scientist
Johnson & Johnson
June 24, 2026
Remote friendly (Bridgewater, NJ)
United States
IT
Purpose
Lead Data Scientist for MedTech Supply Chain Digital to design, develop, and deploy production-grade AI solutions (Generative AI, LLMs, agentic AI, classical ML, computer vision) with measurable business impact.
Responsibilities
- Lead end-to-end AI/ML & GenAI projects: problem framing, requirements, data prep, model development, architecture, production deployment, and post-deployment monitoring/optimization.
- Architect and deliver ML solutions for complex, cross-functional initiatives.
- Design/build/deploy agentic AI systems (multi-agent orchestration, tool-use frameworks, RAG, autonomous decision workflows).
- Run POCs and rapidly prototype ML/GenAI products; transition POCs into production-grade solutions.
- Partner with product, engineering, and business stakeholders on product vision, technical roadmaps, and value delivery.
- Provide technical leadership/mentorship; conduct code/model reviews; establish best practices.
- Author/review technical documents; share knowledge and contribute to AI/ML thought leadership.
- Evaluate emerging AI technologies and drive adoption.
- Establish standards for model governance, responsible AI, reproducibility, and documentation.
Qualifications
Required: PhD (1+ yrs) or MS (3+ yrs) hands-on data science; production deployment of large-scale ML in cloud (Azure preferred); expertise in LLMs/GenAI/agentic AI with LangChain/LangGraph/Semantic Kernel/AutoGen/CrewAI (or similar); Python; ML/data tools (PyTorch/TensorFlow/scikit-learn/Hugging Face; Spark/SQL/Pandas); strong prompt engineering, fine-tuning, RAG/eval frameworks; excellent communication.
Preferred: MLOps/DevOps (CI/CD, model versioning, MLflow/W&B, Docker/Kubernetes, IaC); Azure AI services; responsible AI governance (fairness/explainability); domain experience (demand/supply planning/manufacturing/supply chain); streaming/event-driven AI; publications/patents.
Benefits (as described)
Medical, dental, vision, life insurance, short/long-term disability, business accident insurance, group legal; retirement and savings (401(k)); long-term incentive; paid time off and parental leave (per plan terms).
Lead Data Scientist for MedTech Supply Chain Digital to design, develop, and deploy production-grade AI solutions (Generative AI, LLMs, agentic AI, classical ML, computer vision) with measurable business impact.
Responsibilities
- Lead end-to-end AI/ML & GenAI projects: problem framing, requirements, data prep, model development, architecture, production deployment, and post-deployment monitoring/optimization.
- Architect and deliver ML solutions for complex, cross-functional initiatives.
- Design/build/deploy agentic AI systems (multi-agent orchestration, tool-use frameworks, RAG, autonomous decision workflows).
- Run POCs and rapidly prototype ML/GenAI products; transition POCs into production-grade solutions.
- Partner with product, engineering, and business stakeholders on product vision, technical roadmaps, and value delivery.
- Provide technical leadership/mentorship; conduct code/model reviews; establish best practices.
- Author/review technical documents; share knowledge and contribute to AI/ML thought leadership.
- Evaluate emerging AI technologies and drive adoption.
- Establish standards for model governance, responsible AI, reproducibility, and documentation.
Qualifications
Required: PhD (1+ yrs) or MS (3+ yrs) hands-on data science; production deployment of large-scale ML in cloud (Azure preferred); expertise in LLMs/GenAI/agentic AI with LangChain/LangGraph/Semantic Kernel/AutoGen/CrewAI (or similar); Python; ML/data tools (PyTorch/TensorFlow/scikit-learn/Hugging Face; Spark/SQL/Pandas); strong prompt engineering, fine-tuning, RAG/eval frameworks; excellent communication.
Preferred: MLOps/DevOps (CI/CD, model versioning, MLflow/W&B, Docker/Kubernetes, IaC); Azure AI services; responsible AI governance (fairness/explainability); domain experience (demand/supply planning/manufacturing/supply chain); streaming/event-driven AI; publications/patents.
Benefits (as described)
Medical, dental, vision, life insurance, short/long-term disability, business accident insurance, group legal; retirement and savings (401(k)); long-term incentive; paid time off and parental leave (per plan terms).