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High due to Tier-1 brand, popular Data Scientist title, metro location, and broad GenAI skill requirements.
Medium because core ML/GenAI skills transfer across industries, but supply-chain and regulated pharma experience increases specificity.
High due to mandatory hands-on GenAI/LLM skills, specific frameworks (LangChain), and enterprise/regulatory expectations.
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Design, develop, and deploy advanced AI and machine learning solutions for clinical and commercial supply chain processes at Amgen.
Own end-to-end AI and data science solutions including problem framing, prototype development, validation, deployment, and stabilization with measurable operational impacts.
Collaborate cross-functionally with business, technology, architecture, and data teams to integrate AI capabilities into supply chain applications, workflows, and automation platforms.
Experience developing and applying AI/ML, Generative AI, and analytics solutions for supply chain or similar business problems.
Hands-on skills in building GenAI and LLM-based applications with frameworks like LangChain or LangGraph.
Strong programming skills in Python and experience with AI/ML libraries, APIs, SQL/NoSQL databases, and data pipelines.
Work Experience Required: Not explicitly mentioned in the JD.
Experienced in integrating AI systems into enterprise applications and automating workflows with focus on real-time intelligence and operational efficiency.
Familiarity with AI agent architectures, orchestration patterns, Responsible AI practices, and enterprise AI governance.
Knowledge or prior exposure to pharma, life sciences, or regulated AI environments with compliance frameworks like GxP or HIPAA is a plus.