Lead Data Scientist
Johnson & Johnson
June 24, 2026
Remote friendly (Titusville, NJ)
United States
IT
Purpose
- Lead the design, development, and deployment of production-grade AI solutions (Generative AI, LLMs, agentic AI, classical ML, computer vision) driving measurable business impact across J&J MedTech.
Responsibilities
- Lead end-to-end AI/ML and GenAI projects (problem framing, requirements, data prep, model development, architecture, deployment, monitoring/optimization).
- Architect and deliver ML solutions for complex 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 to production.
- Partner with product/engineering/business to define vision, technical roadmaps, and deliver measurable value.
- Provide technical leadership/mentorship; conduct code/model reviews and set best practices.
- Author/review technical proposals and documents; share knowledge and thought leadership.
- Continuously evaluate emerging AI technologies and drive adoption.
- Establish/enforce standards for model governance, responsible AI, reproducibility, and documentation.
Qualifications
Required:
- PhD (1+ yrs) or MS (3+ yrs) hands-on data science; large-scale ML in cloud (Azure preferred).
- Expertise in LLMs/GenAI/agentic AI; experience with LangChain/LangGraph/Semantic Kernel/AutoGen/CrewAI or similar.
- Production deployment experience (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 genAI evaluation.
- Strong communication for non-technical stakeholders.
Preferred:
- MLOps/DevOps, CI/CD, model versioning, MLflow/W&B, Docker/Kubernetes, infrastructure-as-code.
- Azure AI services (Azure OpenAI, AI Foundry, Azure ML, Cognitive Services).
- Responsible AI (fairness, explainability, bias, governance) at enterprise scale.
- Demand/Supply Planning/manufacturing/supply chain domain experience.
- Real-time/streaming or event-driven AI.
Benefits (explicitly stated)
- Medical, dental, vision, life insurance, short/long-term disability, business accident and group legal insurance; retirement/pension and 401(k); long-term incentive eligibility.
- Time off: vacation, sick time, holiday pay, work/personal/family time, parental leave, condolence, caregiver, volunteer, and military spouse time-off.
Pay Range (stated)
- $109,000–$174,800 USD base pay range.
- Lead the design, development, and deployment of production-grade AI solutions (Generative AI, LLMs, agentic AI, classical ML, computer vision) driving measurable business impact across J&J MedTech.
Responsibilities
- Lead end-to-end AI/ML and GenAI projects (problem framing, requirements, data prep, model development, architecture, deployment, monitoring/optimization).
- Architect and deliver ML solutions for complex 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 to production.
- Partner with product/engineering/business to define vision, technical roadmaps, and deliver measurable value.
- Provide technical leadership/mentorship; conduct code/model reviews and set best practices.
- Author/review technical proposals and documents; share knowledge and thought leadership.
- Continuously evaluate emerging AI technologies and drive adoption.
- Establish/enforce standards for model governance, responsible AI, reproducibility, and documentation.
Qualifications
Required:
- PhD (1+ yrs) or MS (3+ yrs) hands-on data science; large-scale ML in cloud (Azure preferred).
- Expertise in LLMs/GenAI/agentic AI; experience with LangChain/LangGraph/Semantic Kernel/AutoGen/CrewAI or similar.
- Production deployment experience (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 genAI evaluation.
- Strong communication for non-technical stakeholders.
Preferred:
- MLOps/DevOps, CI/CD, model versioning, MLflow/W&B, Docker/Kubernetes, infrastructure-as-code.
- Azure AI services (Azure OpenAI, AI Foundry, Azure ML, Cognitive Services).
- Responsible AI (fairness, explainability, bias, governance) at enterprise scale.
- Demand/Supply Planning/manufacturing/supply chain domain experience.
- Real-time/streaming or event-driven AI.
Benefits (explicitly stated)
- Medical, dental, vision, life insurance, short/long-term disability, business accident and group legal insurance; retirement/pension and 401(k); long-term incentive eligibility.
- Time off: vacation, sick time, holiday pay, work/personal/family time, parental leave, condolence, caregiver, volunteer, and military spouse time-off.
Pay Range (stated)
- $109,000–$174,800 USD base pay range.