Ontology and Data Science Engineer

Indigo Industries Inc

Arlington, VA, United States

about 2 months ago

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Role details

Contract type

Permanent contract

Employment type

Full-time (> 32 hours)

Experience level

Experienced

Experience required

5 years minimum

Working hours

Regular working hours

Job source

www.clearancejobs.com

Tech stack

Systems Engineering Cloud Computing Computer Programming Data Infrastructure Data Structures R (Programming Language) Graph Database Python (Programming Language) Logical Data Models Neo4j Semantic Web SPARQL

+6 more

Systems Modeling Language Systems Architecture Apex Code Pandas Scikit Learn Information Technology

Job description

Ontology Development & Integration: Design, develop, and maintain ontologies to structure complex data, ensuring alignment and integration with overarching Mission Engineering ontologies within the MEIA JCDE environment.
Analytical Modeling: Develop, test, and support advanced analytical and statistical models to assess the performance, gaps, and effectiveness of current and proposed systems and capabilities.
System Modeling: Utilize SysML to support MBSE efforts, mapping system architectures and behaviors to underlying data structures and ontologies.
Data Translation: Act as a bridge between systems engineers and data architects, translating mission requirements into logical data models and quantitative assessments.
Reporting & Visualization: Synthesize complex data science outputs and semantic queries into clear, actionable insights for mission stakeholders and decision-makers.Technical Liaison: Support the APEX by translating mission requirements into technical specifications for enterprise IT partners.

Requirements

Professional Experience:

Professional Experience: Mid-level professional (5-8+ years) with data science, systems engineering, or ontology development experience.
DoD Domain Context: Prior experience supporting DoD/DoW mission sets, processes, or data environments is a strong plus, though not a strict requirement.
Data Science & Modeling Proficiency: Strong proficiency in Statistical Software, data science programming (e.g., Python, Pandas, Scikit-learn, R), and SysML for MBSE efforts.
Semantic Web Expertise: Applied experience with semantic web technologies and ontology languages (e.g., OWL, RDF, SPARQL). Familiarity with graph databases (e.g., Neo4j, ArangoDB) and MBSE software (e.g., Cameo Systems Modeler) is highly desirable., * Education: Bachelor’s or Master’s degree in Data Science, Systems Engineering, Computer Science, Mathematics, or a related technical field.
Certifications: Relevant certifications in Data Science, MBSE (e.g., OCSMP), or Cloud infrastructure are preferred.