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Strong Tier-1 brand, metro location, and a popular Data Scientist title create high competition.
Core ML skills transfer broadly, but supply-chain and regulated pharma context increase specificity moderately.
Mandatory GenAI/LLM, LangChain, deployment, and governance skills raise shortlisting strictness to high.
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Design, develop, and deploy AI/ML solutions, including generative AI and large language models, to support global supply chain decision-making and automation.
Own end-to-end AI and data science projects, managing problem framing, prototype development, validation, deployment, and performance metrics like cycle time and forecast quality.
Collaborate cross-functionally with product, business, technology, and AI platform teams to integrate AI capabilities into supply chain applications and workflows, ensuring scalable and maintainable solutions.
Experience developing AI/ML and generative AI solutions, specifically with large language models, foundation models, predictive modeling, and related AI frameworks.
Hands-on development skills in Python, AI/ML libraries, APIs, SQL/NoSQL databases, and application development.
Experience building GenAI and LLM-based applications such as chatbots, copilots, and RAG pipelines with vector database integration.
Work Experience Required: Not explicitly mentioned in the JD.
Experienced in applied AI for supply chain or related domains, with practical knowledge of AI orchestration frameworks like LangChain or LangGraph.
Strong understanding of responsible AI, model validation, enterprise AI governance, and regulated environments such as pharma or life sciences preferred.
Capable of leading AI projects end-to-end in fast-paced, cross-functional Agile environments with strong communication and stakeholder management skills.