Jobs / United States / Capital One Services LLC
Manager, Ontology and Data Modeling
Capital One Services LLC · 🇺🇸 5 Locations
Sponsorship verdict
Sponsorship possible
One solid signal, not two — worth applying, and worth asking about sponsorship early.
- Employer is on a government sponsor recordThe US Department of Labor certified 838 H-1B/E-3 labor condition applications for this employer between Oct 2025 and Jun 2026 (latest Jun 2026) — the step every H-1B hire needs first. USCIS also records 253 H-1B approvals in FY2023. Source: LCA disclosure data (US Department of Labor (OFLC)).
- The posting doesn’t mention sponsorshipSilence isn’t a refusal — ask the recruiter before investing much time.
- No salary bar for this routeH-1B has no fixed salary bar: the employer must pay at least the prevailing wage for the role and area. Cap-subject employers enter a lottery weighted by wage level. Source: https://www.federalregister.gov/documents/2025/12/29/2025-23853/weighted-selection-process-for-registrants-and-petitioners-seeking-to-file-cap-subject-h-1b, rules effective 2026-02-27.
- What Capital One Services LLC paid sponsored hires in similar roles1 certified filing for “Data Analysis Manager” (Data Scientists) in MA: $162k–$162k, median $162k. Most were filed at wage level IV (100%) — 4 lottery entries, ≈61% projected selection odds for cap-subject employers. Source: US Department of Labor LCA disclosure data (Oct 2025 – Jun 2026).
- Confirmed live todayWhen a source last listed this job as open.
US H-1B: cap-subject employers enter a lottery weighted by wage level — Level I gets 1 entry, Level IV gets 4 (DHS projected selection odds ≈15% at Level I to ≈61% at Level IV). Universities and non-profit research employers are cap-exempt. The $100,000 fee for new petitions from abroad is currently blocked by a court order (appeal pending).
A verdict summarises public evidence; it is not legal advice and never a guarantee — the employer and the immigration authority decide. Sign in to factor in where you can already work.
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Sponsor Radar — Capital One Services LLC
The US Department of Labor certified 838 H-1B/E-3 labor condition applications for this employer between Oct 2025 and Jun 2026 (latest Jun 2026) — the step every H-1B hire needs first. USCIS also records 253 H-1B approvals in FY2023. Source: LCA disclosure data (US Department of Labor (OFLC)).
Past sponsorship or register membership never guarantees sponsorship for this vacancy or for you. Full Sponsor Radar for Capital One Services LLC →
About the role
Manager, Ontology and Data Modeling The role of the Manager of Ontology and Data Modeling is to develop, implement, and maintain enterprise ontologies in support of Capital One's Data Strategy. The Manager of Ontology and Data Modeling, as part of Finance Products and Data Solutions, will be responsible for working collaboratively across Finance and Enterprise partners to develop domain ontologies in support of our ERP replacement initiatives. With this replacement, we are looking for someone to champion the creation and adoption of standardized data. The Manager of Ontology and Data Modeling will be responsible for partnering with Technology, Product, and other Capital One teams to support the development and integration of semantic technology into Capital One products and services. The Manager of Ontology and Data Modeling should be capable of supporting an emerging and evolving semantic program at Capital One, capable of clearly communicating and advocating the value of using semantic technology and knowledge organization concepts. Primary Responsibilities • Define clear and actionable problem statements to help teams deliver results while displaying a comprehensive understanding of ontologies and optimized data models • Leverage customer insights to influence priorities and roadmap development while advocating for and driving alignment between stakeholders in the development of acceptance criteria • Own and prioritize the near-term Ontology and Data Modeling roadmap to deliver on business outcomes, quickly identifying points of leverage in complex problems or systems, and utilizing data effectively to define success metrics and measurable outcomes • Utilize balanced judgment in decisions about risks of both actions taken and not taken while innovating on ways to iterate faster in a well-managed way for the immediate team • Understand and leverage technology and end-state architecture vision in partnership with Technology, Machine Learning, and other Capital One teams to support the development and integration of semantics in Capital One products and services, driving comprehensive design decisions out of white space technical problems • Deliver value by creating reusable, extensible and resilient capabilities and proactively identify opportunities when key metrics are not performing • Develop and communicate a 6-month vision to senior stakeholders and partner teams with accurate details and transparency on risks and impediments, and proactively build relationships with those outside of your immediate team resulting in horizontal influence • Contribute to team culture and recruiting by leading activities to attract and retain top talent and mentoring and developing junior ontology and data modeling associates • Manage teams that develop, implement and govern ontologies and optimized data models in consultation with stakeholder • Contribute to data integration and mapping efforts to harmonize data with Capital One's upper and domain ontologies • Communicate and advocate the value of Capital One's efforts in ontologies, semantics, and standardization across the business. • Maintain awareness of competitor and industry developments related to ontology use, knowledge organization, data modeling, and machine learning • Understand and adhere to W3C standards related to ontologies, in particular RDF, RDFS, OWL, SKOS, and SHACL • Develop standards, guidelines, and direction for ontology, data modeling, semantics and Data Standardization in general at Capital One Role-Based Competencies • Able to develop and implement ontologies and data models in consultation with stakeholders in teams dedicated to data management, search, product management, machine learning, and other enterprise initiatives. • Able to commun