This role pays less than
81%
of similar roles. Most pay
$165,500–$261,375
— the shaded band above.
At the midpoint, this role pays about
$160k
versus about
$213k
for comparable roles.
Based on 240 similar postings.
Employer
About Capital One Financial
Capital One Financial is a bank holding company specializing in credit cards, auto loans, banking, and savings products, known for its data-driven approach to consumer and commercial finance. Industry: Financial Services & Banking
Capital One Financial currently has
998 open roles
on FindRole.
Listed pay typically runs
$197,300–$225,100
across 992 roles with salary data.
Manager, Ontology & Data Modeling joins the Enterprise Products and Platforms team to develop, implement, and maintain enterprise ontologies supporting the corporate data strategy. This role involves collaborating across various business lines to build domain ontologies, integrate semantic technology into products, and manage the ontology and data modeling roadmap. The position requires creating reusable capabilities, defining technical requirements for machine learning teams, and establishing standards for data standardization. Key technical skills include proficiency with W3C standards such as RDF, RDFS, OWL, SKOS, and SHACL, along with experience in SQL or SPARQL. Candidates should be familiar with tools like Protégé, Stardog, or Neptune, and possess knowledge of graph databases and linked data. The role solves complex problems regarding knowledge organization and semantic enrichment to harmonize data across the enterprise while advocating for the value of semantic technology.
Develop, implement, and maintain enterprise ontologies to support corporate data strategy.
Partner with technology and machine learning teams to integrate semantic technologies into products.
Define actionable problem statements and manage the ontology and data modeling roadmap.
Create reusable, extensible, and resilient capabilities for data integration and mapping.
Establish standards, guidelines, and governance for data modeling and standardization.
Advocate for the value of semantic technology and knowledge organization to senior stakeholders.
Manage teams responsible for developing and governing optimized data models.
Conduct research on industry trends regarding graph databases, linked data, and machine learning.
What we're looking for
Bachelor's degree in information science, computer science, engineering, library science, ontology, semantics, or computational linguistics.
At least 4 years of experience in a metadata field such as ontology, taxonomy, semantics, or computational linguistics.
At least 4 years of experience or training in W3C standards including JSON, XML, RDF, RDFS, OWL, and SKOS.
At least 4 years of experience or training in ontology and linked data tools like Protégé, TopQuadrant, PoolParty, Stardog, AnzoGraph, Neptune, or Data.World.
At least 4 years of experience or training with SQL or SPARQL.
Ability to develop, implement, and govern enterprise ontologies and optimized data models.
Ability to communicate and advocate for the value of semantic technology and knowledge organization concepts.
Strong project management skills and ability to lead teams in a collaborative environment.
Ontologies
Knowledge Graphs
RDF
OWL
Semantic Web
RAG
Generative AI
Agentic AI
Metadata Management
Graph Databases
Data Science
Machine Learning
Deep Learning
Data Governance
Statistical Analysis
Time Series Analysis