Lead Data Scientist
Johnson & Johnson
June 24, 2026
Remote friendly (Horsham, PA)
United States
IT
Lead Data Scientist (Data Science)
Purpose
- Lead the design, development, and deployment of production-grade AI solutions (Generative AI/LLMs, agentic AI systems, classical ML, and computer vision) delivering measurable business impact across J&J MedTech.
You Will Be Responsible For
- Collaborate to shape a cohesive digital product and technology strategy enabling product-led transformation and a scalable, reusable, modular, cost-effective digital ecosystem.
In Addition, You Will
- Lead end-to-end AI/ML and GenAI projects (problem framing, requirements, data prep, model development, architecture, production deployment, monitoring/optimization).
- Architect and deliver complex ML solutions across cross-functional projects.
- Design, build, and deploy agentic AI systems (multi-agent orchestration, tool-use, RAG, autonomous decision workflows).
- Run POCs and rapidly prototype ML/GenAI products; translate POCs into production.
- Partner with product/engineering/business stakeholders on product vision, technical roadmaps, and measurable value.
- Provide technical leadership/mentorship; conduct code/model reviews and establish best practices.
- Author/review technical proposals, design docs, reports; share knowledge and thought leadership.
- Evaluate emerging AI technologies and drive adoption.
- Establish standards for model governance, responsible AI, reproducibility, and documentation.
Requirements / Qualifications
Required Skills
- PhD (1+ years) or MS (3+ years) in data science; hands-on building/deploying large-scale ML systems in cloud (Azure preferred).
- Expertise in LLMs/GenAI and agentic AI; hands-on with LangChain/LangGraph/Semantic Kernel/AutoGen/CrewAI (or similar).
- Production deployment experience (model serving, APIs, scalability, monitoring).
- Python; ML libraries (PyTorch, TensorFlow, scikit-learn, Hugging Face) and data tools (Spark, SQL, Pandas).
- Agentic AI depth (multi-agent systems, tool use, planning/reasoning, memory, human-in-the-loop).
- Prompt engineering, LLM fine-tuning, RAG, embeddings, and evaluation frameworks.
- Strong communication and ability to influence non-technical stakeholders.
Preferred Qualifications
- MLOps/DevOps, CI/CD, versioning (model/experiments), MLflow/W&B, Docker/Kubernetes, infrastructure-as-code.
- Azure AI services (Azure OpenAI, AI Foundry, Azure ML, Cognitive Services).
- Responsible AI (fairness, explainability, bias detection, governance).
- Multi-functional partnership; demand/supply planning/manufacturing/supply chain domain.
- Real-time/streaming/event-driven AI; publications/patents (plus).
Benefits (if applicable as stated)
- Medical, dental, vision, life insurance; short-/long-term disability; business accident insurance; group legal.
- Retirement plan and 401(k); long-term incentive program; vacation/sick time, holiday pay, parental leave, and other time-off.
- Learn more: https://www.careers.jnj.com/employee-benefits
Purpose
- Lead the design, development, and deployment of production-grade AI solutions (Generative AI/LLMs, agentic AI systems, classical ML, and computer vision) delivering measurable business impact across J&J MedTech.
You Will Be Responsible For
- Collaborate to shape a cohesive digital product and technology strategy enabling product-led transformation and a scalable, reusable, modular, cost-effective digital ecosystem.
In Addition, You Will
- Lead end-to-end AI/ML and GenAI projects (problem framing, requirements, data prep, model development, architecture, production deployment, monitoring/optimization).
- Architect and deliver complex ML solutions across cross-functional projects.
- Design, build, and deploy agentic AI systems (multi-agent orchestration, tool-use, RAG, autonomous decision workflows).
- Run POCs and rapidly prototype ML/GenAI products; translate POCs into production.
- Partner with product/engineering/business stakeholders on product vision, technical roadmaps, and measurable value.
- Provide technical leadership/mentorship; conduct code/model reviews and establish best practices.
- Author/review technical proposals, design docs, reports; share knowledge and thought leadership.
- Evaluate emerging AI technologies and drive adoption.
- Establish standards for model governance, responsible AI, reproducibility, and documentation.
Requirements / Qualifications
Required Skills
- PhD (1+ years) or MS (3+ years) in data science; hands-on building/deploying large-scale ML systems in cloud (Azure preferred).
- Expertise in LLMs/GenAI and agentic AI; hands-on with LangChain/LangGraph/Semantic Kernel/AutoGen/CrewAI (or similar).
- Production deployment experience (model serving, APIs, scalability, monitoring).
- Python; ML libraries (PyTorch, TensorFlow, scikit-learn, Hugging Face) and data tools (Spark, SQL, Pandas).
- Agentic AI depth (multi-agent systems, tool use, planning/reasoning, memory, human-in-the-loop).
- Prompt engineering, LLM fine-tuning, RAG, embeddings, and evaluation frameworks.
- Strong communication and ability to influence non-technical stakeholders.
Preferred Qualifications
- MLOps/DevOps, CI/CD, versioning (model/experiments), MLflow/W&B, Docker/Kubernetes, infrastructure-as-code.
- Azure AI services (Azure OpenAI, AI Foundry, Azure ML, Cognitive Services).
- Responsible AI (fairness, explainability, bias detection, governance).
- Multi-functional partnership; demand/supply planning/manufacturing/supply chain domain.
- Real-time/streaming/event-driven AI; publications/patents (plus).
Benefits (if applicable as stated)
- Medical, dental, vision, life insurance; short-/long-term disability; business accident insurance; group legal.
- Retirement plan and 401(k); long-term incentive program; vacation/sick time, holiday pay, parental leave, and other time-off.
- Learn more: https://www.careers.jnj.com/employee-benefits