Posted May 29, 2026
Company Overview:
ANSER enhances national and homeland security by strengthening public institutions. We provide thought leadership for complex issues through independent analysis, and we deliver practical, useful solutions. ANSER values collaboration, integrity, and initiative and we are client focused in all that we do. Because we were established for the purpose of public service and not for profit, we measure our success in the impact of our service. 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).
Active TS/SCI clearance with the ability to obtain and maintain a polygraph. - 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. - 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 in support of intelligence or defense missions
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). We seek individuals from a broad variety of backgrounds with varying levels of experience who have a desire to do meaningful work.
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