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Tier-1 brand plus sought-after ML/GenAI skills balanced by niche supply-chain and regulated requirements.
Core ML/AI skills transferable, but pharma supply-chain and compliance requirements raise domain specificity.
Mandatory GenAI/LLM expertise, deployment experience, and regulated-domain familiarity create strict technical filters.
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Design, develop, and deploy AI and data science solutions to enhance clinical and commercial supply chain processes end-to-end.
Lead rapid prototyping and delivery of AI/ML and Generative AI applications including integration into supply chain workflows, APIs, and automation platforms.
Own AI solution lifecycle from problem framing through production deployment, managing scope, risks, technical tradeoffs, and measurable operational outcomes such as forecast accuracy and efficiency.
Work Experience Required: Not explicitly mentioned in the JD.
Hands-on experience with AI/ML, Generative AI, LLMs, including application development like chatbots, copilots, RAG pipelines, and vector DB integration.
Strong Python programming skills and familiarity with AI/ML libraries, APIs, SQL/NoSQL databases, and modern application frameworks.
Experience or preference for regulated environments such as pharma or life sciences; knowledge of compliance aspects like GxP or HIPAA is a plus.
Experienced applied AI Data Scientist skilled in supply chain domain with ability to translate complex business needs into scalable AI-driven solutions.
Proficient in AI agent architectures, orchestration frameworks (e.g., LangChain), and Responsible AI principles, capable of integrating AI capabilities into enterprise workflows.
Comfortable working cross-functionally with product, technical, and business teams, and taking end-to-end ownership in fast-paced, Agile delivery environments.