A Data Scientist utilizes skills and experience to systematically answer questions using data to provide actionable recommendations. Commonly utilizes advanced statistical analysis and machine learning techniques. Common responsibilities also include data cleaning and data management.
Data Ontology & Standards Engineer/Scientist Apogee Engineering, LLC Wright-Patterson AFB, OH Job Details 15 hours ago Qualifications Data model design Data Integration (Data management) Data modeling projects Bachelor's degree Leading team collaboration initiatives Cross-functional team management Cross-functional communication
Full Job Description Overview:
Apogee is seeking a Data Ontology & Standards Engineer/Scientist to Lead the design and governance of mission-focused data ontologies, standards, and knowledge models to enable interoperable, integrated intelligence data across NASIC and partner enterprises. •Contingent Upon Contract Award•
Responsibilities:
Develop and maintain knowledge models, including mission-relevant terms, definitions, hierarchies, and relationships. Define and document data standards that enable consistent data integration and reuse. Collaborate with cross-functional teams (mission analysts, engineers, architects, data owners) to validate and adopt standards. Guide data architecture planning and standard approval processes in coordination with governance bodies. Support integration of ontologies and standards into tools, repositories, and workflows. Produce the monthly Data Ontology Posture Report documenting progress against mission requirements and recommended standards.
Qualifications:
Minimum Experience:
Citizenship:
Must be a US citizen
Clearance:
Ability to obtain and maintain TS/SCI Education /
Years of Experience:
Bachelor's degree in Information Science, Computer Science, Data Science, or related field. 8+ years of experience in data architecture, ontology/metadata design, or enterprise data management. Experience defining and managing controlled vocabularies, taxonomies, or ontologies in complex domains. Strong understanding of data modeling concepts and data integration patterns. Demonstrated ability to lead cross-functional standards and governance efforts.
Preferred Qualifications:
Experience with semantic technologies (e.g., RDF/OWL, knowledge graphs) or standards such as UML, OWL, or SKOS. Background in intelligence data standards or community data models. Experience implementing data standards within cloud or enterprise platforms. Familiarity with MBSE, digital engineering, or analytics platforms that consume standard data models.
