Title: Data Scientist, DIA Capabilities and Requirements
OverviewThe Data Scientist position supports DIA's Command Element by serving as a technical expert focused on strategic decision-making through advanced analytics, requirements management, quality assurance, and AI workflow development.
Primary ResponsibilitiesThe role encompasses four main areas of responsibility:
- Advanced Analytics and Capabilities Development: The data scientist applies statistical methods, machine learning techniques, and data visualization to support capabilities development initiatives. This involves analyzing complex datasets to identify capability gaps, inform resource allocation decisions, and provide quantitative assessments. The position requires translating analytical findings into actionable recommendations that shape DIA's future operational capabilities.
- Requirements Management: The role involves developing and maintaining analytical frameworks to ensure requirements are traceable, measurable, and aligned with strategic objectives. This includes creating data models that capture relationships between user needs, capability requirements, and technical specifications, as well as building dashboards and reporting tools for leadership visibility.
- Quality Assurance: The data scientist establishes testing protocols, validates model outputs, assesses data integrity, and ensures analytical tools meet accuracy and reliability standards. This includes conducting sensitivity analyses, documenting assumptions and limitations, and recommending improvements to existing methodologies.
- AI Workflow Implementation: A critical aspect involves designing and implementing AI workflows that automate routine analytical tasks and enhance decision-making processes. The data scientist evaluates emerging AI technologies for applicability to DIA missions, develops prototypes, and provides technical guidance on responsible AI adoption while ensuring systems are explainable, auditable, and compliant with relevant policies.
Key RequirementsThe position requires extensive collaboration across cross-functional teams including intelligence analysts, program managers, acquisition professionals, and technical experts. Strong communication skills are essential for translating complex technical concepts into clear briefings, written reports, and visual presentations for senior leadership. Additional expectations include mentoring junior analysts, maintaining awareness of emerging analytical techniques, and representing the Command Element in technical working groups and interagency forums. A Bachelor's or Master's degree in Data Science, Computer Science, Statistics, AIML, or another related STEM field is required.
