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# Data Engineer / Data Scientist

- **Company:** Indigo Industries Inc
- **Location:** Arlington, VA, United States
- **Experience:** Experienced
- **Contract:** Permanent contract
- **Skills:** 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, Systems Modeling Language, Systems Architecture, Apex Code, Pandas, Scikit Learn, Information Technology
- **Published:** October 14, 2026
- **Apply:** https://www.clearancejobs.com/jobs/9237819/data-engineer-data-scientist

## About the Role

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 & Certifications:

 * 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.

## 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.