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Tier-1 brand, metro location, mid-level data scientist title, and popular GenAI skillset increase applicant competition.
ML/AI skills transfer broadly, but pharma supply-chain and regulated compliance raise domain specificity.
Requires 5+ years, GenAI/LLM production experience, Responsible AI, and specific tooling expertise.
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Design, develop, and deploy AI/ML applications to optimize clinical and commercial supply chain processes globally.
Own end-to-end AI and data science projects including prototyping, validation, deployment, and stabilization with measurable impact on cycle time, forecast quality, and operational efficiency.
Collaborate cross-functionally with business, product, and technology teams to deliver scalable, maintainable AI-driven decision-support solutions and integrate them into supply chain systems.
5+ years experience applying AI/ML, Generative AI, and analytics to supply chain domain problems with hands-on development.
Hands-on experience with Large Language Models, Generative AI applications (chatbots, copilots, RAG pipelines), and AI orchestration frameworks like LangChain or LangGraph.
Strong proficiency in Python, AI/ML libraries, APIs, SQL/NoSQL databases, and modern application development practices.
Prior experience in pharma, life sciences, or regulated AI environments preferred; familiarity with GxP, HIPAA, or related compliance is a plus.
Technically deep individual contributor with experience delivering end-to-end AI/ML solutions in complex supply chain or regulated environments.
Comfortable bridging technical and non-technical stakeholders, translating complex AI outputs into business insights and recommendations.
Experienced working in Agile teams and global virtual environments, skilled at managing priorities and overcoming technical and organizational challenges for sustained delivery.