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

Responsibilities & Key Deliverables

Key Responsibilities

AI & ML Strategy for Strategic Sourcing

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.

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.

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

Core AI & ML

Expert in Python programming

Strong expertise in:

Machine Learning

Deep Learning

NLP

Generative AI

LLM architectures

Hands-on experience with:

LangChain

Vector databases

RAG pipelines

Prompt engineering

AI orchestration frameworks

Experience with ML frameworks:

TensorFlow

PyTorch

Scikit-learn

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Enterprise Systems

Strong knowledge of:

SAP S/4HANA

Qlik SaaS

3DEXPERIENCE (3DX)

Enterprise data lakes

API integrations

Middleware systems

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Development Skills

Strong React development knowledge

REST API and microservices architecture expertise

Experience with:

FastAPI / Flask

Docker

Kubernetes

CI/CD pipelines

MLOps platforms

Cloud platforms (Azure/AWS/GCP)

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Data & Analytics

SQL and enterprise data modeling expertise

Experience handling large-scale enterprise datasets

Dashboarding and analytical platform integration experience

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Preferred Industry Knowledge

Automotive purchasing and sourcing processes

BOM and cost structure understanding

Supplier ecosystem management

Manufacturing digital transformation

Procurement analytics and spend management

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Behavioral Competencies

Strong problem-solving and analytical mindset

Excellent stakeholder management

Strong communication and presentation skills

Ability to convert business problems into AI-driven solutions

Innovation-oriented with execution focus

Ability to work in fast-paced cross-functional environments

System Generated Core Skills

System Generated Secondary Skills