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AI and ML Data Scientist

Job in McLean, Fairfax County, Virginia, USA
Listing for: Phase2 Technology
Full Time position
Listed on 2026-07-13
Job specializations:
  • Software Development
    AI Engineer (Applied/Software), Machine Learning/ ML Engineer, Data Scientist
Salary/Wage Range or Industry Benchmark: 77600 - 176000 USD Yearly USD 77600.00 176000.00 YEAR
Job Description & How to Apply Below

AI and ML Data Scientist The Opportunity

As an Agentic AI Engineer and Data Scientist for military intelligence, you're excited by the opportunity to design, develop, and deploy advanced AI systems that help analysts transform complex, fragmented information into actionable intelligence. You understand the possibilities created by large language models (LLMs), machine learning (ML), natural language processing (NLP), autonomous workflows, and multi-agent architectures, and you want to apply them to mission‑critical national security challenges.

In today's contested and information‑rich operating environment, military intelligence teams must rapidly make sense of large volumes of structured and unstructured data from multiple sources, formats, and domains. As an AI professional at Booz Allen, you'll help build intelligent systems that support intelligence discovery, analysis, prioritization, reporting, and decision advantage for defense and national security clients.

On our team, you'll use your AI, data science, and software development skills to create real‑world mission impact. You'll work closely with clients, analysts, engineers, and mission stakeholders to understand operational needs, identify high‑value use cases, and develop agentic AI capabilities that can reason over data, orchestrate workflows, retrieve relevant information, generate analytic products, and support human‑in‑the‑loop decision‑making. You'll design and implement AI agents, retrieval‑augmented generation pipelines, evaluation frameworks, prompt strategies, data processing workflows, and mission‑focused prototypes.

You'll help ensure these systems are reliable, explainable, secure, testable, and aligned to operational requirements. Ultimately, you'll help military intelligence organizations use AI responsibly and effectively to accelerate insight, improve analytic tradecraft, and support informed decisions.

You Have
  • Experience developing, integrating, or evaluating AI, ML, NLP, LLMs, or agentic AI capabilities for mission, operational, or enterprise use cases, and building AI‑enabled applications using Python and modern AI/ML libraries or frameworks, including PyTorch, Scikit‑Learn, Lang Chain, Llama Index, Hugging Face, or CUDA
  • Experience developing agentic AI systems, including autonomous or semi‑autonomous agents, tool‑using agents, multi‑step reasoning workflows, task orchestration, retrieval‑augmented generation, or human‑in‑the‑loop AI capabilities
  • Experience analyzing, processing, and integrating structured and unstructured data sources, including intelligence data such as text, reports, messages, metadata, documents, or geospatial data
  • Experience designing, testing, validating, or evaluating AI/ML systems, including model performance, accuracy, relevance, robustness, hallucination mitigation, or mission‑aligned evaluation criteria
  • Experience supporting military intelligence, defense intelligence, all‑source analysis, targeting, indications and warning, collection management, operations intelligence, or national security missions, and developing AI systems for classified, air‑gapped, secure, or operationally constrained environments
  • Experience with prompt engineering, prompt evaluation, model benchmarking, fine‑tuning, synthetic data generation, or LLM application development
  • Knowledge of information retrieval, embeddings, vector databases, semantic search, data labeling, classification models, model evaluation, and data quality assessment
  • Ability to translate military intelligence mission requirements into technical AI solutions, prototypes, and production‑ready capabilities
  • TS/SCI clearance
  • Bachelor's degree in Data Science, CS, AI, ML, Engineering, Operations Research, Applied Mathematics, or Statistics
Nice If You Have
  • Experience with distributed data, cloud, or high‑performance computing tools, including Spark, Kafka, Hadoop, Hive, EMR, Databricks, Kubernetes, Docker, Open Search, Elasticsearch, or similar technologies
  • Experience developing APIs, microservices, analytic interfaces, dashboards, or production software using FastAPI, Flask, REST services, Git, CI/CD, Dev Sec Ops , Plotly, Dash, Streamlit, Tableau, or Power…
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