OneMain Financial Jobs

Job#: 3023612

Job Description:

Job Description

Questions that must be answered and submitted with resume so that manager may review

• Tell me about a time you had to define or clarify a business concept that multiple teams were using differently. What steps did you take, and what artifact did you ultimately produce?
• Describe a data catalog, business glossary, or taxonomy you personally built or curated. What problem was it solving, and how did you know it was successful?
• Tell me about a time when unclear data definitions caused downstream issues (analytics, automation, models, or reporting). How did you fix it, and what changed afterward?

Role Summary

We are seeking an AI & Data Semantics Lead to accelerate our LLM and AI model teams by serving as the critical bridge between business stakeholders, data products, and technical AI teams. This role is responsible for translating complex technical data assets into clear, governed, business-understandable semantics that can be safely and effectively leveraged by AI models. The ideal candidate is exceptionally strong in business analysis, comfortable working in enterprise data catalog environments, and experienced in building taxonomies, business glossaries, and semantic layers that scale across teams and use cases. This role will directly support the success of agentic capabilities, AI use cases, and data product adoption by ensuring models understand what data means, not just where it lives.

Key ResponsibilitiesLLM & 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