Ontologist

Ontologist - Insurance Domain

Level: Senior / Principal

Department: Data Architecture / Enterprise Information Management

Location: London - Hybrid

We have an urgent requirement come from a client for Insurance specific ontology specialists who understand insurance domain very well. So underwriting ontologist, claims ontologist.

Permanent role / SUBCON

Suggestion is try to find someone who really understands subtle difference between data modeling and Ontology.

Key tip: Someone who has worked extensively with Json structures and can understand how data models and Json structure works may fit in the role..

About the Role

We are building a canonical insurance ontology that spans policy, coverage, underwriting, claims, and product taxonomy - intended to serve as the semantic backbone across our data platforms, AI applications, and regulatory reporting. You will own the vocabulary: designing, extending, and governing OWL/RDF ontologies that give every downstream system a shared, machine-readable understanding of what Chubb's insurance concepts mean.

This is a hands-on engineering role, not a purely theoretical one. You will work in JSON-LD and Turtle daily, collaborate with product SMEs to capture domain semantics correctly, and apply formal upper ontologies (gist, PROV-O) to anchor Chubb's terms to open standards.

What You Will Do

- Design and extend the Chubb insurance ontology - classes, properties, named individuals - across lines of business: property & casualty, management liability, professional indemnity, specialty, consumer insurance products and reinsurance.

- Drive vocabulary governance: establish and enforce naming conventions, cardinality rules, namespace strategy, and deprecation policies as the ontology grows.

- Translate SME knowledge into formal axioms: interview underwriters, product managers, actuaries, and claims handlers; convert their business definitions into rdfs:comment, skos:definition, and OWL restrictions.

- Map source schemas to ontology: analyze source system data dictionaries (SQL DDL, Excel, XML/XSD) and produce mappings with rationale - the handoff artefact that drives engineering implementation.

- Collaborate with the data engineering and AI teams to ensure ontology terms are consumable in knowledge graphs, LLM RAG pipelines, and BI semantic layers.

- Maintain provenance and audit trails using PROV-O: every term addition records its rationald it, and the SME who approved it.

- Run validation gates before each ontology release: naming conformance checks, annotation completeness, IRI stability, and backward-compatibility review.

- Contribute to tooling: improve the ontology SDLC pipeline (mapping validators, visualisers,ongside the engineering team.

Required (Must Have)

- 4+ years of hands-on ontology engineering using OWL 2, RDF, RDFS, and SPARQL.

- Proficiency in at least one serialization format: JSON-LD, Turtle, or RDF/XML - JSON-LD pre

- Experience mapping source data schemas (any format) to ontology terms and articulating the design decisions behind each choice.

- Familiarity with at least one upper or mid-level ontology: gist, FIBO, BFO, PROV-O, Dublin

- Ability to communicate ontology decisions in plain business language - you will present to underwriters, not only to engineers.

- Strong written skills: every term you mint needs a clear, non-circular rdfs:comment

Preferred

- Insurance domain knowledge - commercial and consumer insurance products

- Experience with FIBO (Financial Industry Business Ontology) or ACORD data standards and the underlying data models.

- Knowledge of SHACL for ontology constraint validation.

- Familiarity with provenance capture patterns (PROV-O Activities, Entities, Agents).

- Experience building or governing ontologies used in AI / knowledge graph / RAG contexts.

- Python scripting for ontology tooling