Analytic Methodologist - Expert
$118,000–$172,700 year
On-site · Reston, Virginia, United States
Job Summary
Analytic Methodologist (Expert) role focusing on developing analytic strategies to resolve mission-driven intelligence questions within an Object-Based Intelligence program. Responsibilities include deconstructing complex questions to tailor structured analytic methodologies, evaluating and adapting analytic models for objectivity and predictive value, designing and maintaining domain ontologies to enable semantic data representation, and building knowledge graphs to support data querying, visualization, and interoperability. Apply semantic web standards (RDF, OWL, SPARQL) and establish ontology version control and governance in compliance with IC/DoD policies. Collaborate to improve semantic data retrieval and reasoning across knowledge graphs by developing data queries (GraphQL, SPARQL, SHACL, SQL). Contribute to capability development by editing and storing ontologies in Government-owned source repositories. Requires U.S. citizenship and active TS/SCI with CI poly; 20 years of experience and an advanced degree. Preferred qualifications include applied predictive analytics, multi-disciplinary team leadership, and experience with ML/NLP/LLMs and related technologies. Pay is disclosed with ranges for the DC metro area; starting pay aligns with experience and location.
Required Qualifications
- U.S. Citizen
- Active TS/SCI with CI poly
- Active U.S. Government Security Clearance at TS/SCI with CI poly
- Minimum 20 years of experience
- Advanced degree in a related field
- Experience with structured analytic methods
- Familiarity with semantic technologies and ontology development tools (e.g., Protégé)
- Excellent oral and written communication skills
- Experience with Python
- Knowledge of data science applications and architectures
Desired Qualifications
- 20 years of experience
- advanced degree
- U.S. citizen
- active TS/SCI with CI poly
- security clearance
- experience with structured analytic methods
- experience with semantic technologies and ontology development tools (e.g., Protégé)
- Python proficiency
- excellent communication skills
- experience with data storage and various data science applications and architectures
- experience in machine learning, NLP, large language models, Spark, Hadoop, SQL, visualization tools (Tableau) would be a plus
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