Vice President- Ontologist

JPMorgan Chase JPMorgan Chase · Banking · New York, NY +1 · Corporate Sector

JPMorgan Chase is seeking a Vice President-Ontologist to shape their knowledge representation strategy using ontologies and taxonomies to enhance data interoperability and management, preparing data for AI applications. The role involves engaging with domain experts, assessing standard ontologies, and developing organization-wide ontologies, influencing various departments.

What you'd actually do

  1. Development and adoption of ontologies to represent complex domains
  2. Evaluate industry standard ontologies for adoption across JPMC
  3. Work closely with stakeholders, subject matter experts, product owners, and engineers to understand their use cases, requirements, and dependencies, critically assessing proposed solutions
  4. Provide expert input into the JP Morgan Chase’s firmwide data strategy
  5. Communicate complex ideas effectively to collaborators using precise terminology and relatable examples, and ask clarifying questions to define core meanings.

Skills

Required

  • ontology development
  • taxonomy development
  • data interoperability
  • knowledge representation
  • semantic technologies
  • ISO 20022
  • OWL
  • RDF
  • SKOS
  • SHACL
  • Protégé
  • TopBraid Composer
  • PoolParty

Nice to have

  • Master's or Ph.D. in Ontology Engineering, Knowledge Representation, or Semantic Technologies
  • Financial sector data standards and ontologies
  • program management
  • collaborative development best practices
  • large-scale, distributed, end-to-end systems
  • Data Governance
  • Data Management
  • Ontology community contributions

What the JD emphasized

  • 3+ years of experience developing and managing ontologies for real-world applications
  • Expertise in Data and Financial service standards such as ISO 20022, OWL, RDF, SKOS, and SHACL.
  • Experience with ontology and taxonomy development process and tools (e.g., Protégé, TopBraid Composer, PoolParty, etc.).

Other signals

  • preparing our data for AI applications
  • ontology engineering
  • knowledge representation
  • semantic technologies