This role pays less than
97%
of similar roles. Most pay
$156,525–$231,150
— the shaded band above.
At the midpoint, this role pays about
$119k
versus about
$194k
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.
The Senior Associate, Ontology and Data Modeling joins the Finance Products and Data Solutions team to develop, implement, and maintain enterprise ontologies supporting the corporate data strategy. This role involves collaborating with Finance and Enterprise partners to create domain ontologies, championing standardized data, and integrating semantic technology into products and services. The individual will manage data integration and mapping efforts to harmonize information with upper and domain ontologies while advocating for knowledge organization concepts across the business. Key technical requirements include proficiency in W3C standards such as RDF, RDFS, OWL, SKOS, and SHACL, along with experience using tools like Protégé, Stardog, or Neptune. The role also requires skills in SQL, SPARQL, Python, R, and graph databases to solve complex data discoverability and search problems through advanced modeling and semantic enrichment techniques.
Develop, implement, and govern enterprise ontologies and optimized data models to improve data discoverability.
Execute data integration and mapping efforts to harmonize information with upper and domain ontologies.
Integrate semantic technology into company products and services in partnership with Technology and Machine Learning teams.
Advocate for the value of semantic technologies and knowledge organization concepts across the business.
Implement knowledge organization strategies using tools for machine learning, ontology management, and semantic enrichment.
Establish standards, guidelines, and direction for data modeling and general data standardization.
Test and troubleshoot new or updated models and systems to ensure functionality.
What we're looking for
Bachelor's degree in information science, computer science, engineering, library science, ontology, semantics, or computational linguistics.
Master's degree in information science, computer science, engineering, library science, ontology, semantics, or computational linguistics is preferred.
At least 2 years of experience in a metadata field of work or relevant training.
At least 2 years of experience or training in W3C standards including JSON, XML, RDF, RDFS, OWL, and SKOS.
At least 2 years of experience or training in ontology and linked data tools such as Protégé, TopQuadrant, PoolParty, Stardog, AnzoGraph, Neptune, or Data.World.
At least 2 years of experience with SQL, SPARQL, or a combination of both.
Experience with graph databases, Python, R, and cloud platforms like Amazon Web Services is preferred.
Strong communication skills to advocate for semantic technology and explain complex ideas to diverse audiences.
Machine Learning
Deep Learning
LLMs
Generative AI
NLP
Python
Hugging Face
Transformers
PyTorch
TensorFlow
NumPy
Scikit-Learn
Pandas
AWS
SageMaker
Prompt Engineering
Big Data