Data Model Ontologist | Banking

Capco is a global technology and management consultancy specializing in driving digital transformation in the financial services and insurance industries. Capco is committed to providing clients with practical solutions. We offer a globally integrated service with offices in leading financial centers across the globe. We have the people, the vision, and the passion.

We are growing through a significant growth journey, now is a very good time to join us as we expand geographically, increase headcount and disrupt the consulting market across APAC with entrepreneurial and agile thinking.

• Experts in banking and payments, capital markets and wealth and asset management
• Deep knowledge in financial services offering, including e.g. Finance, Risk and Compliance, Financial Crime, Core Banking etc.
• Committed to growing our business and hiring the best talent to help us get there
• Focus on maintaining our nimble, agile and entrepreneurial culture

We are currently seeking Senior Data Consultants to support and drive the growth of our Data practice, particularly in our Data Analysis / Data Modelling stream. This is an exciting opportunity to be a leader, in a growing team of data practitioners, where you will be initiating and implementing cutting-edge data & analytics programmes for top-tier Financial Services clients.

This role sits at the intersection of ontology development, data modeling, AI engineering, and banking domain logic, enabling the creation of knowledge graphs, decision structures, and rule systems that support an enterprise‑wide AI pipeline.

• 6+ years of data ontology modeling experience within Financial Services
• Hands‑on experience with semantic technologies such as TURTLE (TTL), RDF, OWL, SKOS, and SPARQL.
• Strong conceptual data and ontology modeling skills, including hierarchies, constraints, vocabularies, and rule sets.
• Experience designing and working with knowledge graphs and graph platforms (e.g. Neo4j, GraphDB, Stardog, AWS Neptune).
• Proficiency in YAML for structured rule definition, configuration, and schema modeling.
• Familiarity with LLM‑enabled systems, agentic AI workflows, and retrieval‑augmented generation (RAG); experience with decision modeling, rules engines, Python, or AI‑driven automation is a strong advantage.