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The Data Scientist Level 3 will use mathematical, statistical, and computational skills to analyze large datasets, derive insights, and communicate results to both technical and non-technical audiences.

The analyst prepares synthesized products from research and analysis to meet Intelligence Community requirements, collaborates with teams, and maintains customer awareness.

Develop and integrate cyber planning, mitigation strategies, tactics, and operations. Use analytic techniques and tools to create operational campaigns, document use cases, research data sources, coordinate with external partners, communicate requirements, and lead working groups supporting adversary defeat and strategic/operational-level missions.

Perform analytic modeling, statistical analysis, and data engineering to extract value from large, messy datasets. Design and implement ML and inference methods, translate mission needs into technical requirements, and communicate technical findings and recommendations to non-technical stakeholders.

Conduct advanced analysis of collection and open-source data to generate insights, ensure target continuity, and maintain databases. Identify intelligence gaps and apply multiple analysis disciplines.

Serve as principal AI technical advisor to translate emerging AI capabilities into workforce development and mission-focused training. Collaborate with researchers and engineers to define skills, build curriculum, create labs and use cases, support demonstrations and workshops, evaluate technologies, and guide AI governance, MLOps, LLMs, agentic AI, and cybersecurity integration for national security missions.

Develop, maintain, and enhance diverse software systems. Oversee software teams, conduct reviews, ensure quality, and design algorithms according to requirements.

Lead design, development, and deployment of production-grade AI systems for mission-critical cyber and intelligence operations. Architect scalable MLOps pipelines, deploy models to cloud, on‑prem, and edge, integrate AI into cybersecurity workflows, ensure secure and RMF-compliant deployments, mentor engineers, and transition prototypes into operational systems.

Develop analytics from cyber and SIGINT data, using Java and big data technologies. Collaborate with customers to create prototypes and improve data representation.

Responsible for Quality Assurance in training material and developing lesson plans, ensuring compliance and effectiveness in instructional delivery.