Role & responsibilities
Analyst 2+ yrs
Mandatory skills: Enterprise AI + Supply Chain + Data Science
Bangalore/Pune/Mumbai/Noida/Hyderabad
Supply Chain AI Strategy & Use Case Development
- 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.
Client Engagement & Advisory Support
- 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.
Data & AI Foundations
- 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.
EDUCATION
- MBA / Master’s Degree —engineering, supply chain, or information systems preferred.
BASIC (REQUIRED) QUALIFICATIONS
- 0–2 years of experience (including internships, 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.
PREFERRED QUALIFICATIONS
- 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.
Preferred candidate profile
