AI & Data Semantics Lead (Business-Facing) - Remote - Banking - Direct Client - JOBID687
Key Responsibilities
LLM & AI Enablement
• Partner with LLM and AI model teams to define, document, and govern business meaning for data assets used in training, inference, and agentic workflows.
• Translate business concepts into structured semantic artifacts (business terms, classifications, relationships) consumable by AI systems.
• Support responsible AI by ensuring data assets have clear definitions, ownership, lineage context, and usage constraints.
Business Analysis & Stakeholder Engagement
• Lead discovery sessions with business stakeholders to extract domain knowledge and convert it into reusable semantic assets.
• Act as a trusted translator between business leaders, data product owners, engineers, and AI practitioners.
• Decompose ambiguous business questions into well-defined data concepts and analytical intent.
Metadata, Catalog & Taxonomy Development
• Build and maintain enterprise business glossaries, taxonomies, and classification frameworks within a data catalog environment.
• Curate and enrich technical assets with business context (descriptions, relationships, use cases, examples).
• Ensure semantic consistency across domains, data products, and AI use cases.
Data Product & Platform Alignment
• Align semantic definitions with data products, certified assets, and governed data sources.
• Partner with data governance, data quality, and lineage teams to ensure metadata completeness and trust.
• Contribute to standards and patterns for AI'ready metadata and semantic modeling.
Required Qualifications
• 7+ years of experience in business analysis, data analysis, or data product roles
• Demonstrated experience working in a data catalog or metadata management platform (e.g., Alation or equivalent)
• Hands-on experience building:
• Business glossaries
• Taxonomies / classification models
• Semantic layers or conceptual data models
• Strong ability to translate technical data assets into business language
• Proven experience partnering with technical teams (data engineering, analytics, AI/ML)
• Excellent facilitation, documentation, and stakeholder communication skills
Apply Now
Apply Now
LLM & AI Enablement
• Partner with LLM and AI model teams to define, document, and govern business meaning for data assets used in training, inference, and agentic workflows.
• Translate business concepts into structured semantic artifacts (business terms, classifications, relationships) consumable by AI systems.
• Support responsible AI by ensuring data assets have clear definitions, ownership, lineage context, and usage constraints.
Business Analysis & Stakeholder Engagement
• Lead discovery sessions with business stakeholders to extract domain knowledge and convert it into reusable semantic assets.
• Act as a trusted translator between business leaders, data product owners, engineers, and AI practitioners.
• Decompose ambiguous business questions into well-defined data concepts and analytical intent.
Metadata, Catalog & Taxonomy Development
• Build and maintain enterprise business glossaries, taxonomies, and classification frameworks within a data catalog environment.
• Curate and enrich technical assets with business context (descriptions, relationships, use cases, examples).
• Ensure semantic consistency across domains, data products, and AI use cases.
Data Product & Platform Alignment
• Align semantic definitions with data products, certified assets, and governed data sources.
• Partner with data governance, data quality, and lineage teams to ensure metadata completeness and trust.
• Contribute to standards and patterns for AI'ready metadata and semantic modeling.
Required Qualifications
• 7+ years of experience in business analysis, data analysis, or data product roles
• Demonstrated experience working in a data catalog or metadata management platform (e.g., Alation or equivalent)
• Hands-on experience building:
• Business glossaries
• Taxonomies / classification models
• Semantic layers or conceptual data models
• Strong ability to translate technical data assets into business language
• Proven experience partnering with technical teams (data engineering, analytics, AI/ML)
• Excellent facilitation, documentation, and stakeholder communication skills
Apply Now
Apply Now