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AI & Data Semantics Lead; Business-Facing - Remote - Banking - Direct Client
Remote / Online - Candidates ideally in
Cleveland, Cuyahoga County, Ohio, 44101, USA
Listed on 2026-02-28
Cleveland, Cuyahoga County, Ohio, 44101, USA
Listing for:
Outcome Logix ( A Tech 50 Finalist company 2025 and 2022, by Pittsburgh Technology Council )
Remote/Work from Home
position Listed on 2026-02-28
Job specializations:
-
IT/Tech
Data Analyst, Data Science Manager, Data Security
Job Description & How to Apply Below
- 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.
- 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.
- 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.
- 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.
- 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
- 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
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