Principal Ontologist, Graph Modeler

Job not on LinkedIn

🔥 3 minutes ago

🦌 Connecticut, Massachusetts – Remote

🦌 Connecticut – Remote 🍂 Massachusetts – Remote

💵 $145.4k - $218.2k / year

⏰ Full Time

🔴 Lead

🦅 H1B Visa Sponsor

This company has sponsored H1B visas in the past.

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The Hartford

WebsiteLinkedInAll Job Openings

10,000+ employees

Founded 1810

🛡️ Insurance

💸 Finance

👥 B2C

Insurance • Finance • B2C

The Hartford is a well-established insurance company offering a variety of products including auto, home, and business insurance. With over 200 years of experience, it caters to both individuals and small to midsize businesses, providing tailored insurance solutions and employee benefits. The company is particularly known for its AARP-endorsed auto and home insurance programs, which offer exclusive benefits and discounts for members.

📋 Description

• Lead the design and execution of enterprise-scale semantic layers for the Business Insurance data portfolio to standardize business meaning and enable trusted analytics, AI, and agentic use cases. • Define and operationalize ontologies, context graphs, and knowledge graphs across Business Insurance domains to power reasoning, explainability, and decision intelligence. • Model core insurance concepts and relationships spanning customers, accounts, submissions, quotes, policies, coverages, products, risks, claims, producers, and portfolio performance. • Enable semantic-first AI and agentic analytics by ensuring large language models and agents can consume governed business context, metrics, rules, and relationships. • Define canonical semantic vocabularies that standardize meaning across structured and unstructured Business Insurance data sources. • Drive production-scale execution of semantic and graph platforms with standards for performance, governance, security, and lifecycle management. • Define and promote standards and reusable patterns for ontology modeling, graph modeling, semantic interoperability, and ontology reuse across delivery teams. • Partner with Business Insurance data product owners, domain leaders, architects, and engineers to embed semantic models into data products, AI pipelines, analytics, and activation layers. • Work closely with AI Data Architects and AI Data Engineers to operationalize ontologies through graphs, metadata services, APIs, and production data platforms. • Align ontologies and graph models with enterprise data governance, metadata, lineage, quality, privacy, and security standards. • Enable explainability by ensuring AI and analytical outputs can be traced to governed semantic definitions, relationships, rules, and source data. • Serve as the principal authority for semantic engineering, ontology, and graph-modeling practices supporting the Business Insurance data portfolio. • Advance agentic data engineering through reference patterns, playbooks, proofs of value, and production deployments. • Contribute to communities of practice, reference guidance, reusable assets, and internal enablement materials.

🎯 Requirements

• Bachelor’s or Master’s degree in Computer Science, Engineering, Data Science, Information Management, or a related field, or equivalent work experience with large scale data warehouses data. • 8–12+ years of hands-on experience in semantic layer architecture, ontology modeling, graph modeling, and knowledge graph design at enterprise scale. • Deep, hands-on expertise with RDF, OWL (OWL 2), RDFS, SKOS, SPARQL, and W3C semantic web standards. • Proven experience designing and operating enterprise knowledge graphs and governed semantic assets. • Hands-on experience with graph or triple-store technologies such as Neo4j, Amazon Neptune, or Spanner Graph. • Experience integrating knowledge graphs with large language models, retrieval-augmented generation pipelines, vector stores, and agentic frameworks. • Strong understanding of AI consumption patterns, including embeddings, grounding, reasoning, and explainability. • Experience integrating semantic layers with data platforms, APIs, metadata systems, analytics platforms, and AI pipelines. • Ability to translate complex insurance domain knowledge into formal, machine-readable semantic and graph structures. • Strong understanding of context-aware data engineering, canonical modeling, and semantic interoperability. • Proven ability to move from strategy to pilot to scaled enterprise capability. • Strong executive influence and thought leadership in semantic engineering, agentic analytics, and AI-native data engineering. • Hands-on experience with AWS, GCP, and Snowflake. • Business Insurance domain knowledge across one or more areas such as underwriting, policy, claims, distribution, product, customer, or portfolio management. • Excellent communication, presentation, collaboration, and technical leadership skills. • Candidate must be authorized to work in the US without company sponsorship. • The company will not support the STEM OPT I-983 Training Plan endorsement for this position.

🏖️ Benefits

• Short-term or annual bonuses • Long-term incentives • On-the-spot recognition • Perks & Benefits