I&P GN - SC&E – Analyst - Enterprise AI Value Strategy-EVS

You are curious about how artificial intelligence is reshaping the way global supply chains are designed, planned, and operated. You understand that the future of supply chain is not just about automation — it's about intelligent systems that learn, adapt, and collaborate. You bring a blend of functional supply chain knowledge and a growing fluency in enterprise AI concepts, and you're energized by the challenge of turning that combination into tangible value for clients.

You're comfortable moving between structured analysis and open-ended problem-solving. You ask good questions, synthesize complex information quickly, and communicate your thinking clearly — whether you're mapping a demand-planning process, drafting a functional specification, or helping a client imagine what an AI-powered supply chain could look like. You're eager to grow, take direction well, and understand that great consulting outcomes are built on meticulous preparation and disciplined thinking.

Utilize relevant AI tools across all tasks and deliverable creation, including the creation of agents and other tools to help facilitate:

• Identify, assess, and prioritize AI use cases across supply chain domains — Demand Planning, Supply Planning, Manufacturing, Procurement, Aftermarket, and Fulfillment — by mapping current-state processes to AI-enabled future states.
• Support the development of Business Requirements Documents (BRDs) and Functional Requirements Documents (FRDs) grounded in supply chain functional knowledge and client-specific context.
• Contribute to AI reference architecture designs tailored for supply chain environments, illustrating how agentic AI components interact with enterprise data platforms, ERP systems, and planning tools.
• Assist in crafting AI value cases and business cases that articulate ROI, risk, and transformation timelines for supply chain-specific AI initiatives.

• Support client workshops and discovery sessions by preparing materials, capturing requirements, and synthesizing stakeholder inputs across supply chain functions.
• Prepare client-facing presentations, roadmaps, and strategy decks that translate AI and data concepts into accessible narratives for supply chain and operations leaders.
• Apply Design Thinking principles to facilitate structured problem definition and solution ideation sessions with client teams.
• Maintain and evolve the team's repository of supply chain AI frameworks, benchmarks, and industry case examples.

• Develop foundational fluency in enterprise data concepts — data products, data pipelines, and agentic AI hierarchies — as they apply to supply chain planning and execution systems.
• Support data analysis tasks to surface insights from supply chain datasets (e.g., forecast accuracy, inventory performance, supplier scorecards) in service of client recommendations.
• Explore and apply prompt engineering and RAG (Retrieval-Augmented Generation) techniques to build or enhance AI tools that support supply chain advisory workflows.
• Complete assigned AI literacy and continuous-learning modules, contributing to a culture of applied innovation within the team.

• 1.5- 4years of experience (co-ops, or coursework) in supply chain management, operations, business analysis, or a related field.
• Demonstrated functional understanding of at least one supply chain domain: Demand Planning, Supply Planning, Manufacturing, Procurement, Aftermarket, or Fulfillment / Logistics.
• Familiarity with core AI concepts — including Agentic AI fundamentals, AI use case identification, and AI reference architecture at a conceptual level.
• Experience writing or contributing to structured business documents such as process maps, requirements documents, or functional specifications — in an academic or professional setting.
• Demonstrated ability to work with and synthesize data into clear, structured insights or recommendations.
• Experience using AI tools (e.g., GenAI platforms, AI-assisted research or productivity tools) in an academic or professional context.
• Strong written and verbal communication skills with an ability to explain complex concepts clearly to non-technical audiences.

• MBA or Master's degree in Supply Chain, Business Analytics, Information Systems, or a related discipline.
• Coursework, certifications, or self-directed learning in AI, machine learning, or data platforms (e.g., cloud certifications, AI/ML specializations).
• Exposure to consulting environments through internships, case competitions, or strategy project work — with demonstrated ability to structure problems and communicate recommendations.
• Familiarity with enterprise planning or ERP platforms (e.g., SAP IBP, o9, Kinaxis, Blue Yonder, Oracle SCM) in an academic or professional context.
• Participation in supply chain case competitions, AI hackathons, or strategy projects with measurable outcomes.
• Working knowledge of data visualization or analytics tools (e.g., Power BI, Tableau, Python, SQL) applied in a supply chain or operations context.
• Understanding of Prompt Engineering or Retrieval-Augmented Generation (RAG) techniques — even at a foundational or experimental level.

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