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Tier-1 employer, common Data Scientist title, and metro role increase applicant density.
Core ML/LLM skills are highly transferable across industries despite supply-chain context.
Explicit 7-10 years and many mandatory ML/LLM technical requirements enforce strict filtering.
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Lead the design and deployment of advanced AI/ML solutions to solve complex supply chain challenges with measurable business impact.
Architect scalable data science projects aligned to business objectives, including predictive models and LLM-powered applications.
Provide technical leadership and mentorship ensuring rigorous model evaluation, bias mitigation, and production integration of AI systems.
Bachelor's degree in Statistics, Mathematics, Computer Science, Data Science, or related quantitative field.
7-10 years professional experience in data science or analytics with expertise in statistical analysis and business application.
Hands-on experience building and deploying generative AI/LLM applications, including agentic AI systems and RAG pipelines.
Expertise in Python (Pandas, Scikit-learn, PyTorch/TensorFlow), SQL, and system design for production AI pipelines.
Experienced in architecting and operationalizing advanced AI/ML solutions within supply chain or operational efficiency contexts.
Demonstrates deep expertise in generative AI technologies, prompt engineering, and multi-agent autonomous AI workflows.
Capable of translating complex analytics into clear business insights and leading cross-functional AI engineering teams.