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ANSER · 1 week ago

Principal Computer Scientist

Reston, VA

Full-time

Onsite

Lead/Staff

20+ years exp

ANSER enhances national and homeland security by strengthening public institutions. They are seeking a Principal Computer Scientist to support AI/ML Quality Assurance Framework efforts by integrating various scientific techniques to analyze intelligence data and provide guidance on best practices for AI system development.

ConsultingNational SecurityNon ProfitPublic SafetyRisk Management

Comp. & Benefits

No H1B

Security Clearance Required

U.S. Citizen Only

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)

Qualification

Data ScienceMachine LearningPythonPredictive ModelingData VisualizationStatistical AnalysisData MiningKnowledge GraphsAI/ML ModelsDoD ComplianceTraining DevelopmentCommunication SkillsCollaboration

Required

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

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)

Company

ANSER

In 1958 the Air Force needed a technically qualified unbiased organization that could rapidly provide analysis for identified and evolving mission requirements.

Founded in 1958

Falls Church, Virginia, USA

501-1000 employees