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Ontology Remote Jobs (NOW HIRING)

Staff Analytics Engineer

$159K - $187K/yr

Founded in 2016, Kin is a remote-first employer with Kinfolk across more than 35 states. We serve ... Own the hardest modeling and architecture in your team's scope - ontology objects (types ...

Remote Duration: 6+ Months Required Skills * 8-10+ years of experience in backend development using ... Experience working on Knowledge Graph or semantic systems, including ontology-driven design and ...

... Remote). Please review the below and contact me ASAP if you are interested. Job ID:26-18900 Pay ... Configure and support Palantir Ontology, data pipelines, and platform services. * Establish ...

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Ontology Remote information

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$77K

$112.7K

$122K

How much do ontology remote jobs pay per year?

As of Jun 28, 2026, the average yearly pay for ontology remote in the United States is $112,707.00, according to ZipRecruiter salary data. Most workers in this role earn between $106,000.00 and $121,000.00 per year, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive as an Ontology Remote, and why are they important?

To thrive as an Ontology Remote Specialist, you need a solid background in data modeling, knowledge representation, and semantic technologies, often supported by a degree in computer science, information science, or a related field. Familiarity with tools and standards like OWL, RDF, SPARQL, and ontology development platforms such as Protégé is typically required. Strong analytical thinking, attention to detail, and effective communication skills help you collaborate remotely and translate complex concepts for diverse teams. These skills are vital to ensure precise data integration, interoperability, and successful remote teamwork in knowledge-driven organizations.

How does working remotely as an Ontology Specialist impact collaboration and communication with team members?

As a remote Ontology Specialist, you will frequently collaborate with cross-functional teams, such as data engineers, software developers, and subject matter experts, often using digital communication tools like Slack, Zoom, and project management platforms. Clear and proactive communication is essential, as you may work across different time zones and need to document your work thoroughly to ensure alignment. Regular check-ins, virtual meetings, and shared documentation help maintain effective teamwork and ensure that ontology models are developed and integrated smoothly. Adapting to asynchronous communication and being responsive to feedback are common challenges, but they also foster independence and strong organizational skills.

What are ontology remote jobs?

Ontology remote jobs involve working with the design, development, and management of ontologies—structured frameworks for organizing information—while operating from a location outside of a traditional office setting. Professionals in these roles may create data models, standardize vocabularies, and ensure data consistency across systems, often supporting projects in fields like knowledge management, artificial intelligence, healthcare, or libraries. Remote ontology specialists typically collaborate with teams through digital communication tools and may work for tech companies, research organizations, or consulting firms. These positions require strong analytical skills and a background in information science, computer science, or related areas.

What is the difference between Ontology Remote vs Data Analyst?

AspectOntology RemoteData Analyst
Required CredentialsBachelor's in Computer Science, Data Science, or related field; knowledge of ontology modelingBachelor's in Statistics, Mathematics, or related field; proficiency in data analysis tools
Work EnvironmentRemote, often collaborative with cross-disciplinary teamsRemote or on-site, working with data sets and reporting tools
Industry UsageUsed in AI, semantic web, and knowledge management projectsUsed across finance, healthcare, marketing, and more for data insights

Ontology Remote professionals focus on developing and managing ontologies for AI and knowledge systems, requiring specialized understanding of semantic structures. Data Analysts interpret data to inform business decisions, often using statistical tools. While both roles may work remotely and require analytical skills, Ontology Remote emphasizes semantic modeling, whereas Data Analysts focus on data interpretation and reporting.

More about Ontology Remote jobs
What cities are hiring for Ontology Remote jobs? Cities with the most Ontology Remote job openings:
What are the most commonly searched types of Ontology jobs? The most popular types of Ontology jobs are:
What states have the most Ontology Remote jobs? States with the most job openings for Ontology Remote jobs include:
Infographic showing various Ontology Remote job openings in the United States as of June 2026, with employment types broken down into 75% Full Time, and 25% Contract. Highlights an 100% Remote job distribution, with an average salary of $112,707 per year, or $54.2 per hour.

Enterprise Solutions Graph Database

H R PUNDITS INC

Collegeville, PA • On-site, Remote

Full-time

Posted 26 days ago


Job description

Job title : Enterprise Solutions Graph Database/ Architect
Location: Upper Providence Township, PA
(Onsite/Remote )
Experience : 15 Years
Role Overview
Seeking a seasoned Graph Database
Knowledge Graph Expert to perform a comprehensive study of our existing platform. Evaluate our current architecture, data ontology, and query performance to provide a strategic roadmap. The goal is to evolve our Knowledge Graph into a robust, scalable engine that accelerates different Pharma areas ( drug discovery, clinical insights, and cross-departmental data democratization)
Required Qualifications
Graph Expertise: 10+ years of experience with Graph Databases. Deep proficiency in LPG (Labeled Property Graphs) or RDF/Triple Stores.
Pharma Domain Knowledge: Proven experience handling biomedical data types (e.g., Gene-Disease associations, Chemical compounds, Patient journeys).
Semantic Web Standards: Strong understanding of Linked Data principles, URI strategies, and ontology modeling.
Data Engineering: Experience with ETL/ELT pipelines that feed graphs from unstructured (PDF publications) and structured (EDC, LIMS) sources.
Advanced Analytics: Experience implementing Graph Data Science algorithms (centrality, community detection) or integrating Graphs with Machine Learning.
Technical Stack Preferences
Graph DBs: AnzoGraph, Neo4j, Stardog,
Languages: Python, Java, SPARQL, Cypher, or Gremlin.
Bio-Ontologies: Familiarity with OBO Foundry, ChEMBL, or Ensembl.