Digitization & Analytics Manager - Digitization & Analytics Manager - Strategic Sourcing

Responsibilities & Key Deliverables

• Key Responsibilities
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• AI & ML Strategy for Strategic Sourcing
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Partner closely with Purchasing, Commodity Teams, Supplier Quality, Cost Engineering, and Strategic Sourcing stakeholders to identify AI/ML use cases and business transformation opportunities.

• Understand and map procurement processes including:
• RFQ management
• Supplier evaluation
• Spend analytics
• Cost optimization
• Contract analytics
• Demand forecasting
• Supplier risk monitoring
• Procurement operations automation
• Define AI roadmap aligned with organizational digital transformation goals.
• Build scalable AI frameworks and reusable AI components for sourcing functions.
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• AI/ML Solution Development
• Design, develop, and deploy AI/ML applications for procurement and sourcing functions.
• Develop predictive, prescriptive, and generative AI solutions using structured and unstructured enterprise data.
• Build intelligent copilots and AI assistants for procurement users using LLM technologies.
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• Implement:
• NLP models
• Recommendation systems
• Forecasting models
• Supplier intelligence engines
• Semantic search systems
• Document intelligence solutions
• Generative AI workflows
• Create AI-enabled dashboards and analytical insights platforms.
• Large Language Model (LLM) & GenAI Responsibilities
• Architect and implement enterprise-grade LLM applications.
• Fine-tune and optimize LLMs for procurement-specific use cases.
• Build Retrieval-Augmented Generation (RAG) frameworks using enterprise data sources.
• Integrate AI copilots with sourcing workflows and enterprise systems.
• Develop prompt engineering frameworks and AI governance standards.
• Evaluate open-source and commercial GenAI ecosystems for enterprise adoption.
• Ensure responsible AI, security, compliance, and data governance.
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• Enterprise Systems Integration
• Lead integration of AI applications with enterprise platforms including:
• SAP S/4HANA
• Qlik SaaS
• 3DEXPERIENCE (3DX)
• PLM systems
• Supplier portals
• Internal analytics platforms
• Develop API-based architectures and middleware integrations.
• Collaborate with IT, Digital, Data Engineering, and Cloud teams for enterprise deployment.
• Ensure scalability, cybersecurity, reliability, and performance optimization.
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• Full Stack & Application Development
• Lead development of AI-powered web applications and user interfaces.
• Build scalable front-end solutions using React.
• Develop backend AI services and APIs using Python.
• Implement cloud-native and microservices-based architectures.
• Drive DevOps and MLOps best practices for continuous deployment and monitoring.
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• Stakeholder & Team Management
• Work cross-functionally with sourcing leaders, business users, digital teams, and external partners.
• Conduct workshops to identify automation and AI opportunities.
• Mentor data scientists, AI engineers, and analysts.
• Drive vendor evaluations and technology partnerships.

Preferred Industries

Education Qualification

Bachelor’s or Master’s degree in: Computer Science, Artificial Intelligence, Data Science, Information Technology, Electronics Engineering or related field

Preferred:MBA or specialization in Supply Chain / Analytics / AI

General Experience

• 8–15 years of experience in AI/ML, analytics, or enterprise digital transformation.
• Strong experience in manufacturing, automotive, procurement, or supply chain environments preferred.
• Proven track record of delivering enterprise AI applications.

Critical Experience

• Technical Skills
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• Core AI & ML
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• Expert in Python programming
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• Strong expertise in:
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• Machine Learning
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• Deep Learning
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• NLP
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• Generative AI
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• LLM architectures
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• Hands-on experience with:
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• LangChain
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• Vector databases
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• RAG pipelines
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• Prompt engineering
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• AI orchestration frameworks
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• Experience with ML frameworks:
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• TensorFlow
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• PyTorch
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• Scikit-learn
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• Enterprise Systems
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• Strong knowledge of:
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• SAP S/4HANA
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• Qlik SaaS
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• 3DEXPERIENCE (3DX)
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• Enterprise data lakes
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• API integrations
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• Middleware systems
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• Development Skills
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• Strong React development knowledge
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• REST API and microservices architecture expertise
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• Experience with:
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• FastAPI / Flask
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• Docker
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• Kubernetes
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• CI/CD pipelines
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• MLOps platforms
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• Cloud platforms (Azure/AWS/GCP)
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• Data & Analytics
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• SQL and enterprise data modeling expertise
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• Experience handling large-scale enterprise datasets
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• Dashboarding and analytical platform integration experience
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• Preferred Industry Knowledge
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• Automotive purchasing and sourcing processes
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• BOM and cost structure understanding
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• Supplier ecosystem management
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• Manufacturing digital transformation
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• Procurement analytics and spend management
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• Behavioral Competencies
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• Strong problem-solving and analytical mindset
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• Excellent stakeholder management
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• Strong communication and presentation skills
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• Ability to convert business problems into AI-driven solutions
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• Innovation-oriented with execution focus
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• Ability to work in fast-paced cross-functional environments

System Generated Core Skills

System Generated Secondary Skills