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Semantic Modeling Jobs (NOW HIRING)

Semantic Modeler

Arlington, VA · On-site

$120K - $135K/yr

Lead semantic modeling for complex client projects from start to finish * Drive use case development, conducting discovery sessions to identify key model entities to inform initial model drafting

Semantic Modeler

Arlington, VA · On-site

$120K - $135K/yr

Lead semantic modeling for complex client projects from start to finish * Drive use case development, conducting discovery sessions to identify key model entities to inform initial model drafting

$80 - $100/hr

Research and Development Working Model: Hybrid Requisition ID: 13255 Build the Semantic Foundation of the Digital Product Lifecycle The Corporate PLM Office and the Center of Competence (CoC) PLM are ...

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Semantic Modeling information

See salary details

$55.5K

$118.7K

$173.5K

How much do semantic modeling jobs pay per year?

As of Sep 10, 2026, the average yearly pay for semantic modeling in the United States is $118,674.00, according to ZipRecruiter salary data. Most workers in this role earn between $97,500.00 and $133,500.00 per year, depending on experience, location, and employer.

What is semantic modeling?

Semantic modeling is the process of creating structured representations of data that capture the meaning, relationships, and context of information within a specific domain. It involves defining entities, attributes, and the connections between them, often using ontologies or conceptual models. Semantic modeling is widely used in areas like knowledge graphs, data integration, and artificial intelligence to ensure that systems can interpret and use data accurately. By providing a common understanding of data, semantic models enable better interoperability, data quality, and decision-making across different applications.

What are the key skills and qualifications needed to thrive as a semantic modeler, and why are they important?

To thrive as a Semantic Modeler, you need a strong background in data modeling, ontology design, and domain-specific knowledge, often supported by a degree in computer science or information science. Familiarity with semantic web technologies such as RDF, OWL, SPARQL, and tools like Protégé is typically required, along with experience in database management systems. Analytical thinking, attention to detail, and effective communication are essential soft skills for collaborating with stakeholders and translating complex requirements into structured models. These skills ensure the creation of accurate, reusable, and scalable semantic models that support data interoperability and meaningful information retrieval.

What are some common challenges faced by professionals working in semantic modeling, and how can they be addressed?

Professionals in Semantic Modeling often encounter challenges such as aligning diverse data sources, ensuring consistency in ontologies, and effectively communicating complex models to non-technical stakeholders. Addressing these challenges typically involves collaborating closely with domain experts, using standardized vocabularies, and leveraging tools that support visualization and validation of semantic structures. Regular team reviews and iterative refinement of models can also help ensure accuracy and usability, making collaboration and adaptability key aspects of success in this field.

What is the difference between Semantic Modeling vs Data Modeling?

AspectSemantic ModelingData Modeling
PurposeFocuses on capturing meaning and relationships within data to improve understanding and interoperabilityDefines how data is structured, stored, and accessed in databases
CredentialsOften requires knowledge of ontologies, knowledge representation, and sometimes domain-specific expertiseTypically requires understanding of database design, normalization, and data architecture
Work EnvironmentUsed in knowledge graphs, AI, and semantic web projectsUsed in relational, NoSQL, and data warehouse environments
Industry UsageCommon in AI, semantic web, and information integration projectsCommon in software development, database administration, and data engineering

Semantic Modeling and Data Modeling are related but serve different purposes. Semantic Modeling emphasizes understanding and representing the meaning of data, often used in AI and knowledge systems. Data Modeling focuses on structuring data efficiently within databases. Both are essential for effective data management but are applied in different contexts.

What other helpful pages are available for Semantic Modeling?

Other pages related to Semantic Modeling:

Infographic showing various Semantic Modeling job openings in the United States as of September 2026, with employment types broken down into 75% Full Time, and 25% Contract. Highlights an 100% In-person job distribution, with an average salary of $118,674 per year, or $57.1 per hour.

Semantic Modeler

Arlington, VA • On-site

Enterprise Knowledge
11 - 50 employees

$120K - $135K/yr

Full-time

Re-posted 11 days ago


Job description

Enterprise Knowledge (EK) is hiring a full-time Semantic Modeler to join our growing Semantic Design and Modeling Practice. In this role, you will be responsible for supporting semantic model development for client projects across the full model development spectrum, from initial use case development and discovery, through model drafting, validation, and implementation, to developing a governance plan for ongoing model improvement. You’ll work with cleared federal agencies to develop strategies, guide implementation, and apply agile principles to translate business needs into clear, actionable plans.

As with all of our positions, we seek independent thinkers with exceptional written and oral communication skills. This position demands a deep understanding of business strategy and development, experience with knowledge & data management technology solutions, business analysis, and consulting skills.

As an EKer, you will join a fast-growing company that is committed to equity and inclusion, have the opportunity to work in a collaborative workplace, take advantage of our unique benefits, and help build our innovative culture. To read more about the impactful work we are doing and to see the latest thought leadership from EK, follow us on LinkedIn.

Responsibilities
  • Lead semantic modeling for complex client projects from start to finish
  • Drive use case development, conducting discovery sessions to identify key model entities to inform initial model drafting 
  • Conduct knowledge asset analysis activities (such as corpus analysis) to gauge model relevancy 
  • Lead validation activities to engage project stakeholders and client subject matter experts (SMEs)
  • Work closely with engineering teams (internal and/or client-side) to support and ensure optimal model implementation
  • Develop governance plans to inform the ongoing maintenance and scaling of semantic models 
  • Additionally, contribute to EK’s robust Knowledge Base by developing thoughtful and impactful Thought Leadership

Requirements

The candidate must have an active Top Secret SCI clearance.

As a federal contractor, Enterprise Knowledge will not sponsor a new applicant for employment authorization or offer any immigration related support for this position (i.e., H1B, F-1 OPT, F-1 STEM OPT, F-1 CPT, J-1, TN, E-2, E-3, L-1, and O-1, or any EADs or other forms of work authorization that require immigration support from an employer.

This hybrid role requires that you live within a comfortable, commutable distance of our Arlington, VA office and be willing to work in a "SCIF" (Sensitive Compartmented Information Facility) up to 5 days per week.

Required Skills and Experience:
  • At a minimum, candidates must have 6-8 years of relevant work experience (which may include time spent earning relevant advanced degrees)
  • Previous semantic modeling experience (which may include the development of metadata, taxonomies/ thesauri, content models, data models, and/or ontologies) for enterprise-scale applications 
  • Proven success applying information architecture best practices 
  • Familiarity with best practices in knowledge management 
  • Proven experience analyzing, evaluating, and optimizing enterprise search 
  • Ability to communicate advanced concepts to a variety of audiences in a variety of formats, from interpersonal communication to visual modes, including lightweight wireframes
  • Willingness and ability to develop new skills, especially ontology and knowledge graph development 
Preferred Skills and Experience:
  • Knowledge of best practices and approaches for search analytics 
  • Application of user testing/ user research to inform UI/UX strategy 
  • Strong data modeling skills 
  • Advanced visual design skills to convey complex subjects 
  • Experience developing and deploying an auto-tagging initiative to support asset findability and discoverability
  • Experience leveraging Generative AI to support semantic model development and evaluation while retaining explainability 
  • Advanced degree(s) in Information Science/ Library and Information Science, Engineering/Data Management, Data Engineering, Linguistics,  Philosophy, or similar
  • Content modeling experience 
  • Work experience in archives, records management, special collections, or similar
Salary Information:

EK considers a broad range of factors in considering employee salary, including a candidate’s skills, experience, education, certifications, past successes, and qualifications. The salary range for this role is $120,000 to $135,000, with most candidates likely to fall in the lower half. This range does not guarantee a specific salary and may be adjusted based on the needs of the company and the candidate’s qualifications.

Data Privacy Notice:

Enterprise Knowledge (EK) is committed to protecting your personal information. When you submit your application, we collect and process your personal data solely for recruitment and hiring purposes. We will not use your information for any other purpose without your explicit consent.

We may share your information with third parties only as necessary to evaluate your application or comply with legal requirements. If we need to use your data for a purpose beyond the original intent or disclose it to additional third parties, we will provide you with prior notice. 

You have the right to access the personal information we hold about you and to request corrections, amendments, or deletion of any inaccurate data or data processed in violation of applicable privacy principles. Requests for such changes will be reviewed and accommodated unless the burden or expense of providing access would be disproportionate to the risks to your privacy, or where the rights of other individuals may be affected.

By submitting your application, you acknowledge that you have read and understood this notice. If you have any questions about how we handle your personal data or need to update your information, please contact us at careers@enterprise-knowledge.com.