Position Summary

ANSER is seeking an All-Source Analyst to conduct spatially enabled, all-source intelligence analysis to assess, interpret, forecast, and explain national security issues of regional or functional significance for the Defense Intelligence Agency (DIA). In this role you will develop, apply, and maintain Object-Based Intelligence (OBI) governance, standards, and tradecraft to produce integrated, data-driven analytic products that enhance decision-making across the Defense Intelligence Enterprise (DIE).

Day-to-Day Responsibilities

• Conduct all-source analysis using spatially enabled and multi-source intelligence data to support DIA’s analytic and operational requirements.
• Support the development of OBI governance documentation, tradecraft standards, and practitioner training materials.
• Apply DIA and Intelligence Community (IC) analytic tradecraft and style standards to ensure compliance with OBI governance and reference documentation.
• Utilize structured analytic techniques to challenge assumptions, identify biases, and strengthen analytic rigor and confidence in assessments.
• Correlate intelligence results into narrative, visual, and geospatial products that meet DNI analytic tradecraft standards and DIA finished intelligence requirements.
• Retrieve, integrate, and analyze data from multiple classified and unclassified sources using advanced analytic and data science methods.
• Synthesize multi-domain and multi-variant data into coherent, tradecraft-compliant all-source intelligence assessments.
• Exploit large, complex spatial and temporal data sets to produce intelligence supporting DIA and broader Defense Intelligence Enterprise mission objectives.
• Collaborate with DIA functional and regional offices, Combatant Commands, and other IC elements to ensure analytic consistency and concurrence.
• Support DIA efforts to evaluate and validate emerging programs, capabilities, and analytic methodologies relevant to OBI.

Required Qualifications

• Active TS//SCI eligibility with Counterintelligence (CI) Polygraph.
• 12 or more years of experience conducting all-source intelligence analysis at the operational or strategic level.
• Master’s Degree (or bachelor’s degree and additional five years of experience in lieu of a master’s for a total of 17 years’ experience)
• Demonstrated deep knowledge of DIA and IC analytic tradecraft, standards, and publication processes.
• Proficiency in applying structured analytic techniques and producing tradecraft-compliant analytic products.
• Demonstrated experience with research, writing, and briefing skills, with the ability to develop clear and concise analytic narratives.
• Experience documenting analytic workflows to develop ontologies.
• Demonstrated familiarity with Intelligence Community Directive (ICD) 203 standards for analytic integrity and tradecraft.

Preferred Qualifications

• Experience integrating geospatial, temporal, and data science methodologies into all-source analysis.
• Demonstrated ability to collaborate across multiple organizations and coordinate analytic efforts across regional and functional boundaries
• Developing OBI governance and tradecraft to assist DIA and other DIAAE organizations conducting OBI.
• Working with in support of Defense Intelligence All-source Analytic Enterprise (DIAAE) OBI efforts, the Defense Intelligence Enterprise Knowledge Model (DIEKM), and Defense Intelligence Core Ontology (DICO).
• Working with software engineers, data engineers, and data scientists.

Position Summary
ANSER is seeking a Data Scientist to advance analytic efficiency and predictive capabilities across the Object-Based Intelligence (OBI) enterprise. You will leverage data science, machine learning, and statistical techniques to analyze, model, and visualize complex multi-INT datasets, delivering actionable insights that support OBI analytic production and decision-making.

Day-to-Day Responsibilities

• Design, develop, and evaluate advanced algorithmic intelligence, data science, and AI techniques to support Object-Based Intelligence (OBI) through all-source analytic tradecraft, assessments, production, and dissemination.
• Propose and apply advanced statistical, mathematical, and experimental methodologies to identify alternatives, formulate models, and develop innovative analytic techniques.
• Research, prototype, and evaluate technologies that augment or automate all-source analytic processes using computer models and advanced analytics.
• Leverage novel technologies (e.g., large language models, NLP, machine learning) to automate and enhance ontologies, entity recognition, extraction, and summarization in accordance with analytic tradecraft standards.
• Develop, refine, and optimize semantic data retrieval and reasoning across knowledge graphs using query languages and protocols (e.g., SPARQL, GraphQL, SHACL, SQL).
• Evaluate data science, AI, and analytic methods for bias, risk, limitations, and potential distortion of analytic conclusions, and support responsible AI practices.
• Execute Test, Evaluation, Verification, and Validation (TEVV) protocols to assess system performance, robustness, fairness, and tradecraft compliance in all-source analysis contexts.
• Develop, track, analyze, and interpret qualitative and quantitative performance metrics to identify trends, gaps, and opportunities for system improvement.
• Collaborate with stakeholders to implement data-driven decision-making processes and best practices for system development, testing, deployment, and continuous improvement.
• Develop and refine methodologies for evaluating analytic systems, including validation, reasoning completeness, coverage, consistency, and fairness.
• Use data engineering, mining, exploratory, predictive, statistical, and scientific techniques to correlate data and produce graphical, written, visual, and verbal analytic products.
• Write and maintain Python or R scripts, use SQL, manage and merge disparate data sources, and develop scalable workflows for large, spatial, and multi-INT datasets.
• Create and operate in distributed analytic environments, scaling algorithms to handle datasets exceeding system memory constraints.
• Work with ambiguous and complex information by deconstructing key questions, exploiting APIs and spatial data, suggesting methodologies, and developing data schemas.
• Provide consultation, governance guidance, documentation review, audit findings, and version-controlled code contributions to advance OBI standards, knowledge modeling, and DIA analytic capabilities.

Required Qualifications

• TS/SCI with CI Poly clearance
• Bachelor’s degree in in Data Science, Computer Science, Statistics, Mathematics, or related technical field.
• Eight or more years of experience in data science, analytics, or machine learning in support of intelligence or defense missions.
• Proficiency in Python, R, and SQL, and experience with data visualization tools such as Power BI or Tableau.
• Demonstrated understanding of Object Based Intelligence frameworks.
• Demonstrated experience with predictive modeling, data mining, statistical analysis, and ML algorithms.
• Familiarity with knowledge graphs, semantic data modeling, and query languages (e.g., SPARQL, GraphQL).
• Experience developing, implementing, and evaluating AI/ML models for analytic efficiency and tradecraft compliance.
• Experience with large data multi-INT analytics, machine learning (ML), and automated predictive analytics
• Skilled in data visualization and use of graphical applications, including Microsoft Office (Power BI) and Tableau; major data science languages, such as R and Python; managing and merging of disparate data sources, preferably through R, Python, or SQL; statistical analysis; and data mining algorithms.

Preferred Qualifications

• Experience supporting DIA, IC, or DoD analytic modernization or OBI initiatives.
• Knowledge of TEVV methodologies, bias detection, and fairness analysis for AI systems.
• Experience with distributed data processing, cloud-based analytics, or large-scale machine learning architectures.
• Knowledge of DoD 8570/8140 compliance and responsible AI policy frameworks.
• Working with in support of Defense Intelligence All-source Analytic Enterprise (DIAAE) OBI efforts, the Defense Intelligence Enterprise Knowledge Model (DIEKM), and Defense Intelligence Core Ontology (DICO).
• Developing OBI governance and tradecraft to assist DIA and other DIAAE organizations conducting OBI.

Position Summary

ANSER is seeking a Senior Computer Scientist to support AI/ML Quality Assurance Framework (QAF) efforts by integrating mathematics, statics, information science, AI, network science, probability modeling, data mining, data engineering, data warehousing, data compression, data protection, and/or other scientific techniques to correlate complex, technical findings into graphical, written, visual and verbal narrative products on trends of existing intelligence data to leverage other IC data sources.

Day-to-Day Responsibilities

• Review and evaluate QAF documentation submitted by Advanced Analytic (AA) owners to ensure compliance with tradecraft standards and adherence to best practices in AI system development and deployment.
• Assess QAF documentation for completeness, accuracy, and thoroughness, and provide detailed feedback to AA owners and developers.
• Develop and utilize and data mining algorithms based on open-source capabilities. Integrates or codes algorithms to support Government intelligence search and discovery missions.
• Make best practice recommendations on managing data within hardware, software, storage, and bandwidth constraints.
• Assist in maintaining a repository of QAF documentation to facilitate knowledge sharing and best practices across the organization.
• Provide consultation and guidance to AA owners, developers, and stakeholders on the QAF process, including best practices for Al system development, testing, and
• Collaborate with AA owners and developers to identify and address potential issues or gaps in QAF documentation.
• Develop and deliver training materials and workshops to educate AA owners, developers, and stakeholders on the QAF process and its application in AI system development.
• Assist analytic methodologists and AA owners in translating technical documentation into analytic tradecraft compliant language.
• Collaborate with stakeholders to develop, implement, and refine best practices for
• translating technical documentation into tradecraft compliant language.
• Review and edit translated documentation to ensure accuracy, completeness, and
• adherence to tradecraft standards.
• Support capability development by contributing, editing, and storing code in
• Government owned/controlled source version control repositories.
• Employ data science techniques to support predictive analysis, social across the Defense Intelligence Enterprise (DIE).

Required Qualifications

• TS/SCI with Poly Clearance
• Master’s degree in Data Science, Computer Science, Statistics, Mathematics, or related technical field.
• Twelve or more years of experience in data science, analytics, or machine learning in support of intelligence or defense missions.
• Proficiency in Python, R, and SQL, and experience with data visualization tools such as Power BI or Tableau.
• Strong experience with predictive modeling, data mining, statistical analysis, and ML algorithms.
• Experienced with knowledge graphs, semantic data modeling, and query languages (e.g., SPARQL, GraphQL).
• Experience developing, implementing, and evaluating AI/ML models for analytic efficiency and tradecraft compliance.

Preferred Qualifications

• Experience supporting DIA, IC, or DoD analytic modernization or OBI initiatives.
• Working knowledge of TEVV methodologies, bias detection, and fairness analysis for AI systems.
• Experience with distributed data processing, cloud-based analytics, or large-scale machine learning architectures.
• Demonstrated understanding of Object Based Intelligence frameworks.
• Experience with DoD 8570/8140 compliance and responsible AI policy frameworks.
• Experience working with in support of Defense Intelligence All-source Analytic Enterprise (DIAAE) OBI efforts, the Defense Intelligence Enterprise Knowledge Model (DIEKM), and Defense Intelligence Core Ontology (DICO).
• Developing OBI governance and tradecraft to assist DIA and other DIAAE organizations conducting OBI.

Position Summary

ANSER is seeking a Senior Computer Scientist to support AI/ML Quality Assurance Framework (QAF) efforts by integrating mathematics, statics, information science, AI, network science, probability modeling, data mining, data engineering, data warehousing, data compression, data protection, and/or other scientific techniques to correlate complex, technical findings into graphical, written, visual and verbal narrative products on trends of existing intelligence data to leverage other IC data sources.

Day-to-Day Responsibilities

• Design and execute Testing, Evaluation, Verification, and Validation (TEW) protocols
• to evaluate the performance, robustness, and fairness of AI systems in all source analysis ’contexts.
• Collaborate with the Statistician/Mathematician to develop and apply statistical models and methods to analyze TEW results and identify areas for improvement.
• Develop and implement corrective actions to address TEW findings and ensure AI
• system performance and robustness.
• Develop and implement AI system maintenance schedules to ensure continued system performance and robustness.
• Collaborate with stakeholders to identify and prioritize AI system improvements and updates.
• Develop and implement AI system updates and improvements to ensure compliance with
• tradecraft standards and best practices.
• Conduct technical assessments to ensure compliant use of AI systems for approved use
• cases in all source analysis.
• Evaluate AI system performance and adherence to tradecraft standards, and identify areas for improvement.
• Develop and maintain a repository of audit findings and recommendations to facilitate
• knowledge sharing and best practices across the organization.
• Support capability development by contributing, editing, and storing code in
• Government owned/controlled source version control repositories.
• Employ data science techniques to support predictive analysis, social across the Defense Intelligence Enterprise (DIE).

Required Qualifications

• TS/SCI with Poly Clearance
• Master’s degree in Data Science, Computer Science, Statistics, Mathematics, or related technical field.
• Twelve or more years of related experience in data science, analytics, or machine learning in support of intelligence or defense missions.
• High Proficiency in Python, R, and SQL, and experience with data visualization tools such as Power BI or Tableau.
• Strong knowledge of TEVV methodologies, bias detection, and fairness analysis for AI systems.
• Experience with predictive modeling, data mining, statistical analysis, and ML algorithms.
• Experience with knowledge graphs, semantic data modeling, and query languages (e.g., SPARQL, GraphQL).
• Experience developing, implementing, and evaluating AI/ML models for analytic efficiency and tradecraft compliance.
• Understanding of DoD 8570/8140 compliance standards for computer science and cybersecurity roles.

Preferred Qualifications

• Experience supporting DIA, IC, or DoD analytic modernization or OBI initiatives.
• Experience with distributed data processing, cloud-based analytics, or large-scale machine learning architectures.
• Demonstrated understanding of Object Based Intelligence frameworks.
• Experience with DoD 8570/8140 compliance and responsible AI policy frameworks.
• Experience working with in support of Defense Intelligence All-source Analytic Enterprise (DIAAE) OBI efforts, the Defense Intelligence Enterprise Knowledge Model (DIEKM), and Defense Intelligence Core Ontology (DICO).

Position Summary

ANSER is seeking a Principal Computer Scientist to support AI/ML Quality Assurance Framework (QAF) efforts by integrating mathematics, statics, information science, AI, network science, probability modeling, data mining, data engineering, data warehousing, data compression, data protection, and/or other scientific techniques to correlate complex, technical findings into graphical, written, visual and verbal narrative products on trends of existing intelligence data to leverage other IC data sources.

Day-to-Day Responsibilities

• Review and evaluate QAF documentation submitted by Advanced Analytic (AA) owners to ensure compliance with tradecraft standards and adherence to best practices in AI system development and deployment.
• Assess QAF documentation for completeness, accuracy, and thoroughness, and provide detailed feedback to AA owners and developers.
• Develops and utilizes and data mining algorithms based on open-source capabilities. Integrates or codes algorithms to support Government intelligence search and discovery missions.
• Makes best practice recommendations on managing data within hardware, software, storage, and bandwidth constraints.
• Assist in maintaining a repository of QAF documentation to facilitate knowledge sharing and best practices across the organization.
• Provide consultation and guidance to AA owners, developers, and stakeholders on the QAF process, including best practices for Al system development, testing, and deployment.
• Collaborate with AA owners and developers to identify and address potential issues or gaps in QAF documentation.
• Develop and deliver training materials and workshops to educate AA owners, developers, and stakeholders on the QAF process and its application in AI system development.
• Assist analytic methodologists and AA owners in translating technical documentation into analytic tradecraft compliant language.
• Collaborate with stakeholders to develop, implement, and refine best practices for translating technical documentation into tradecraft compliant language.
• Review and edit translated documentation to ensure accuracy, completeness, and adherence to tradecraft standards.
• Supports capability development by contributing, editing, and storing code in Government owned/controlled source version control repositories.
• Employs data science techniques to support predictive analysis, social across the Defense Intelligence Enterprise (DIE).

Required Qualifications

• TS/SCI with Poly Clearance
• Master’s degree in Data Science, Computer Science, Statistics, Mathematics, or related technical field.
• A minimum of 20 years related experience in data science, analytics, or machine learning in support of intelligence or defense missions.
• High knowledge of TEVV methodologies, bias detection, and fairness analysis for AI systems.
• High Proficiency in Python, R, and SQL, and experience with data visualization tools such as Power BI or Tableau.
• High experience with predictive modeling, data mining, statistical analysis, and ML algorithms.
• Strong experience with knowledge graphs, semantic data modeling, and query languages (e.g., SPARQL, GraphQL).
• Strong experience developing, implementing, and evaluating AI/ML models for analytic efficiency and tradecraft compliance.
• Strong understanding of DoD 8570/8140 compliance standards for computer science and cybersecurity roles.

Preferred Qualifications

• Experience supporting DIA, IC, or DoD analytic modernization or OBI initiatives.
• Experience with distributed data processing, cloud-based analytics, or large-scale machine learning architectures.
• Demonstrated understanding of Object Based Intelligence frameworks.
• Experience with DoD 8570/8140 compliance and responsible AI policy frameworks.
• Experience working with in support of Defense Intelligence All-source Analytic Enterprise (DIAAE) OBI efforts, the Defense Intelligence Enterprise Knowledge Model (DIEKM), and Defense Intelligence Core Ontology (DICO).

Position Summary

ANSER is seeking a Data Engineer to design, build, and optimize enterprise-level data management systems to support Object-Based Intelligence (OBI) analytic processes and mission requirements. You will focus on integrating and maintaining scalable, secure data pipelines and architectures that enable advanced analytic workflows, visualization, and automation.

Day-to-Day Responsibilities

• Manage complex, long-term projects involving the design, development, integration, and installation of new information systems, databases, and data services.
• Perform technical studies, systems analysis, and feasibility assessments to ensure designs meet user requirements and define specifications for new or existing data and content management solutions.
• Design, develop, integrate, install, and optimize data management capabilities, data integration solutions, and both relational and non-relational databases (e.g., PostgreSQL) to support enterprise ingestion, storage, retrieval, and analytics.
• Collaborate with team members to design, refine, implement, and maintain resilient, scalable ETL pipelines using industry-standard tools and frameworks (e.g., Apache NiFi).
• Ensure ETL pipelines support secure data acquisition, normalization, enrichment, and delivery while meeting security controls, SLA requirements, and evolving data architecture needs.
• Collaborate with team members to design, implement, and maintain GraphQL APIs enabling flexible, efficient access and aggregation of data across distributed enterprise sources.
• Conduct testing and promote the integration of new databases and data services within existing IT infrastructure, including operational readiness testing and transitional user support.
• Create, execute, and document comprehensive test plans covering component, integration, system, compatibility/interface, user acceptance, and performance/stress testing.
• Monitor, maintain, and upgrade data services, content management systems, and databases; analyze system and database reports to ensure optimal performance.
• Identify data redundancy and design solutions to integrate or consolidate sources, reducing storage and maintenance costs while improving enterprise consistency.
• Produce technical data, performance reporting, and analysis outlining the operational characteristics of databases and data services across the DIA/DIE infrastructure.
• Develop and maintain disaster recovery and continuity plans to ensure data availability, access reliability, and database integrity during crisis situations.
• Analyze, evaluate, and provide recommendations, artifacts, and integration patterns for current, planned, and emerging data service, data management, and database technologies based on performance, cost, and security requirements.
• Design, develop, test, and implement unstructured data management solutions, including content extraction, tagging, data integration, web services, service versioning, containerization (e.g., Docker, Kubernetes), and infrastructure-as-code automation.
• Troubleshoot service, database, and user interface failures; implement temporary fixes and permanent corrections; interface with vendors, developers, and users; manage change requests; support code repositories; and prepare and present technical briefings to senior leadership.

Required Qualifications

• TS/SCI with Poly Clearance
• Bachelor’s degree in Computer Science, Data Engineering, Information Systems, or a related technical discipline.
• Eight (8) or more years of experience in data engineering.
• Proven experience developing and managing data pipelines, ETL processes, and database systems for large-scale or mission-critical environments.
• Proficiency in Python, R, and SQL, and experience with data visualization tools such as Power BI or Tableau.
• Experience with data orchestration and automation tools (e.g., Apache NiFi, Airflow, or similar).
• Familiarity with knowledge graphs, semantic data modeling, and query languages (e.g., SPARQL, GraphQL).
• Experience developing, implementing, and evaluating AI/ML models for analytic efficiency and tradecraft compliance.
• Strong understanding of data security, access control, and system hardening in accordance with DoD and IC standards.
• Demonstrated ability to apply semantic data modeling and metadata standards within an OBI or analytic environment.
• Proficiency in containerization and orchestration technologies such as Docker and Kubernetes.

Preferred Qualifications

• Master’s degree in Data Science, Computer Engineering, or related field.
• Familiarity with semantic web technologies (RDF, OWL, SPARQL) and their use in OBI data integration.
• Understanding of advanced analytic method augmentation.
• Experience developing data visualization and analytic tools supporting structured and unstructured intelligence data.
• Certification in Data Management or Cloud Architecture (e.g., AWS Certified Data Engineer, Google Professional Data Engineer).
• Ability to communicate technical data management concepts clearly to both technical and non-technical audiences.
• Experience supporting DIA, IC, or DoD analytic modernization or OBI initiatives.
• Experience with distributed data processing, cloud-based analytics, or large-scale machine learning architectures.
• Experience working with in support of Defense Intelligence All-source Analytic Enterprise (DIAAE) OBI efforts, the Defense Intelligence Enterprise Knowledge Model (DIEKM), and Defense Intelligence Core Ontology (DICO).
• Experience developing OBI governance and tradecraft to assist DIA and other DIAAE organizations conducting OBI.