Ontologist
About AI TalentFlow
AI TalentFlow is not just about filling roles; we're about building the future of data-driven businesses. We accelerate startup growth, scale enterprise solutions, and nurture the careers of the brilliant minds who make it all happen. Our success is your success, and we are committed to empowering our clients with exceptional talent in AI, Data, Analytics, Product, and... Agile.
The Opportunity:
We are seeking an experienced Ontologist to develop and maintain formal representations of knowledge within specific domain, starting with Life Science and Health Care. You will collaborate closely with subject matter experts, data scientists, and software engineers to evaluate, design, implement, and manage ontologies that enable our clients data-driven initiatives.
Responsibilities:
Design and develop formal ontologies and vocabularies using W3C Standards (OWL, RDF, RDFS, SKOS, SHACL).
Analyze data from various sources and business use cases to identify entities, relationships, and attributes.
Create a clear and consistent conceptual model to represent domain knowledge, informed by common, well-used public ontologies and vocabularies.
Collaborate with subject matter experts to ensure ontologies accurately reflect real-world concepts.
Maintain and evolve existing ontologies to accommodate new information and changing needs.
Document ontologies thoroughly for future use and understanding.
Qualifications:
Master's degree in Computer Science, Information Science, Knowledge Management, or a related field (or equivalent experience).
Strong understanding of knowledge representation, ontology engineering principles, and semantic web technologies and W3C Standards
Experience working with data modeling languages (e.g., UML) and query languages (e.g., SPARQL, Cypher).
Excellent analytical and problem-solving skills.
Ability to work independently and as part of a team.
Strong written and verbal communication skills.
Additional points:
Experience with specific knowledge graph platforms.
Experience with data curation, mapping and transformation tools
Understanding of FAIR Data Implementation patterns
Familiarity with public ontologies, especially in publishing and data representation.
Familiarity with Life Science ontology repositories, such as NCBO and EBI-OLS
Experience developing data playbooks and training materials
Apply Now
AI TalentFlow is not just about filling roles; we're about building the future of data-driven businesses. We accelerate startup growth, scale enterprise solutions, and nurture the careers of the brilliant minds who make it all happen. Our success is your success, and we are committed to empowering our clients with exceptional talent in AI, Data, Analytics, Product, and... Agile.
The Opportunity:
We are seeking an experienced Ontologist to develop and maintain formal representations of knowledge within specific domain, starting with Life Science and Health Care. You will collaborate closely with subject matter experts, data scientists, and software engineers to evaluate, design, implement, and manage ontologies that enable our clients data-driven initiatives.
Responsibilities:
Design and develop formal ontologies and vocabularies using W3C Standards (OWL, RDF, RDFS, SKOS, SHACL).
Analyze data from various sources and business use cases to identify entities, relationships, and attributes.
Create a clear and consistent conceptual model to represent domain knowledge, informed by common, well-used public ontologies and vocabularies.
Collaborate with subject matter experts to ensure ontologies accurately reflect real-world concepts.
Maintain and evolve existing ontologies to accommodate new information and changing needs.
Document ontologies thoroughly for future use and understanding.
Qualifications:
Master's degree in Computer Science, Information Science, Knowledge Management, or a related field (or equivalent experience).
Strong understanding of knowledge representation, ontology engineering principles, and semantic web technologies and W3C Standards
Experience working with data modeling languages (e.g., UML) and query languages (e.g., SPARQL, Cypher).
Excellent analytical and problem-solving skills.
Ability to work independently and as part of a team.
Strong written and verbal communication skills.
Additional points:
Experience with specific knowledge graph platforms.
Experience with data curation, mapping and transformation tools
Understanding of FAIR Data Implementation patterns
Familiarity with public ontologies, especially in publishing and data representation.
Familiarity with Life Science ontology repositories, such as NCBO and EBI-OLS
Experience developing data playbooks and training materials
Apply Now