AI Techno Functional - Supply Chain Master Data -- 100% Remote -- W2 profiles

Role: AI Techno Functional analyst - Supply Chain Master Data
Location: 100% Remote
Key Responsibilities

1. Supply Chain Master Data Management

• Demonstrate strong functional understanding of Supply Chain Master Data, including Material/Product, Customer, Vendor/Supplier, Plant, Bill of Materials (BOM), Unit of Measure (UOM), sourcing, procurement, and reference data.

• Understand master data creation, maintenance, governance, and lifecycle management across supply chain operations.

• Analyze relationships and dependencies between different master data objects.

• Identify data inconsistencies, duplication, missing attributes, and incorrect master data records.

• Understand the impact of master data changes on procurement, manufacturing, inventory management, logistics, and order fulfillment.

• Work with business teams to establish master data standards, ownership, and governance policies.

2. SAP Master Data & Functional Expertise

• Possess hands-on experience working with SAP master data in SAP ECC or SAP S/4HANA environments.

• Understand SAP master data structures, dependencies, business rules, and validation requirements.

• Work with SAP functional teams across relevant modules such as SAP MM, SD, PP, and related supply chain processes.

• Analyze SAP master data fields, attributes, relationships, and integration dependencies.

• Identify data quality issues impacting SAP business transactions and downstream systems.

• Support master data validation, reconciliation, and remediation activities.

• Translate SAP functional requirements into clear technical and data specifications.

3. Data Quality & Governance

• Identify and define Critical Data Elements (CDEs) across supply chain master data domains.

• Translate business requirements into measurable data quality rules and validation logic.

• Define data quality dimensions such as accuracy, completeness, consistency, uniqueness, validity, and timeliness.

• Establish business rules and data validation checks for critical master data attributes.

• Identify root causes of data quality issues and recommend corrective actions.

• Develop data remediation workflows and exception-handling processes.

• Collaborate with data governance teams to establish data ownership, accountability, and quality standards.

• Monitor data quality metrics and provide recommendations for continuous improvement.

4. AI & Intelligent Data Solutions

• Collaborate with AI/ML engineers and technical teams to identify opportunities for AI-driven master data quality improvements.

• Translate business problems into functional requirements for AI-powered data validation and remediation solutions.

• Identify opportunities to leverage AI and automation for duplicate detection, anomaly identification, data classification, and data enrichment.

• Support the design of intelligent data quality frameworks using business rules and AI-based validation approaches.

• Define business scenarios, expected outcomes, and acceptance criteria for AI-enabled solutions.

• Validate AI-generated recommendations and ensure alignment with business rules and supply chain requirements.

• Work with technical teams to improve data quality processes through intelligent automation.

5. Business Analysis & Stakeholder Management

• Engage with supply chain business stakeholders to understand existing processes, challenges, and data requirements.

• Conduct requirement-gathering sessions and translate business needs into functional specifications.

• Prepare business requirement documents (BRDs), functional requirement documents (FRDs), process flows, and use cases.

• Coordinate with SAP functional consultants, data engineers, data architects, and AI development teams.

• Facilitate discussions between business and technical teams to ensure clear understanding of requirements.

• Support functional testing, user acceptance testing (UAT), and business validation.

• Communicate project progress, risks, dependencies, and implementation updates to stakeholders.

Required Skills & Qualifications

• Strong experience in Supply Chain Master Data Management.

• Hands-on knowledge of SAP master data and related business processes.

• Strong understanding of Material/Product, Customer, Vendor/Supplier, Plant, BOM, and UOM master data.

• Knowledge of sourcing, procurement, and supply chain operations.

• Understanding of SAP ECC and/or SAP S/4HANA.

• Familiarity with SAP MM, SD, and PP modules.

• Experience defining Critical Data Elements (CDEs).

• Strong knowledge of Data Quality, Data Governance, and Master Data Management (MDM).

• Ability to define business validation rules, data quality checks, and remediation workflows.

• Experience translating business requirements into functional and technical specifications.

• Understanding of AI/ML concepts and their application in enterprise data management.

• Excellent analytical, problem-solving, communication, and stakeholder management skills.

Preferred Skills

• Experience with AI-driven data quality and master data management initiatives.

• Knowledge of Generative AI, Machine Learning, and intelligent automation.

• Experience with SAP MDG (Master Data Governance).

• Familiarity with data governance and quality platforms.

• Knowledge of SQL and enterprise data platforms.

• Experience with SAP integration and downstream data dependencies.

• Experience working in Agile project environments.