Lead Data Scientist

Johnson & Johnson Innovative Medicine Supply Chain (IMSC) Data Science and AI group is seeking a skilled and motivated Lead Data Scientist to play a key role in our transformation journey. In this position, you will apply innovative analytics to drive business improvement and create a competitive advantage, enhancing data‑driven decision‑making across the supply chain and beyond. The ideal candidate will work closely with business stakeholders to understand requirements, explore and experiment with cutting‑edge AI/ML solutions, and clearly communicate methodologies and results to both technical and non‑technical audiences.

• Collaborate with cross‑functional teams to understand business challenges and requirements, identify AI‑driven opportunities, and ensure effective deployment of AI solutions.
• Experiment and implement cutting‑edge AI/ML solutions (such as natural language processing, deep learning, and predictive analytics, graph) to transform structured and unstructured data into business‑critical insights.
• Continuously review and analyze academic research and industry publications, evaluate state‑of‑the‑art AI/ML methodologies, and prototype innovative solutions to address real‑world business problems.
• Evaluate and refine AI models to enhance accuracy, efficiency, trustfulness and business impact in decision‑making processes.
• Clearly articulate methodologies, results, and insights to non‑technical users and stakeholders, and present AI‑driven recommendations to senior leadership to ensure strategic alignment and impact.

• Bachelor’s degree in statistics, applied mathematics, computer science, engineering, or a related quantitative discipline is required.
• Master’s or PhD in a quantitative field such as statistics, applied mathematics, computer science, engineering, or a related discipline from an accredited college or university is preferred.
• 4–6 years of industry experience solving business problems through the application of statistical modeling, machine learning, deep learning, generative AI, and Retrieval‑Augmented Generation (RAG) techniques.

• Advanced knowledge of traditional machine learning and deep learning foundations and algorithms, including classification, regression, clustering, transformer, reinforcement learning, and anomaly detection.
• Solid understanding of Natural Language Processing (NLP) techniques and Generative AI (GenAI) applications.
• Strong hands‑on experience with Python and relevant packages (e.g., Transformers, Lang Chain, Lang Graph, AG2, vLLM, pydantic, etc.).
• Excellent communication and presentation skills, with the ability to convey complex technical concepts to both technical and non‑technical audiences.
• Excellent problem‑solving skills and ability to work collaboratively in a team setting.

• Deep understanding of agentic AI approaches, including the development of AI agents.
• Exposure to containerization technologies (e.g., Docker) and cloud platforms (e.g., Azure) is a plus.
• Working knowledge of vector databases (e.g., Elasticsearch, Pinecone, FAISS, Weaviate) for information and knowledge retrieval.
• Strong familiarity with Git and version control best practices, with the ability to write clean, maintainable, and well‑documented code.
• Solid understanding of RESTful API design principles and web service architecture.

• May require up to 10% of domestic and international travel.

• Advanced Analytics
• Business Intelligence (BI)
• Coaching
• Collaborating
• Critical Thinking
• Data Analysis
• Database Management
• Data Privacy Standards
• Data Reporting
• Data Savvy
• Data Science
• Data Visualization
• Econometric Models
• Process Improvements
• Technical Credibility
• Technologically Savvy
• Workflow Analysis