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As a Cybersecurity Data Scientist, you will operate as a hands‑on technical contributor and applied research leader responsible for designing, developing, and operationalizing data‑driven and AI‑enabled solutions for Booz Allen's Cyber Operations teams. This role emphasizes execution and delivery, turning security telemetry, threat intelligence, and analyst workflows into production‑grade models, detections, and decision‑support capabilities that measurably improve prevention, detection, response, and recovery outcomes.

You will bridge data science and security operations by translating analyst needs, threat models, and incident learnings into reproducible data pipelines, feature sets, ML/LLM models, and evaluation frameworks deployed across cloud, network, endpoint, identity, and application telemetry domains. You will originate, facilitate, and lead cross‑functional efforts to mature AI‑enabled cybersecurity capabilities, including detection engineering augmentation, alert triage, threat hunting, and SOC automation, while guiding teams through threat‑informed model development, secure‑AI engineering, and responsible AI practices.

Perform model and solution reviews, provide technical direction for complex analytics initiatives, including SIEM, SOAR, and EDR data science integrations, cloud‑native security analytics, and GenAI tooling for analysts, and translate findings into actionable, measurable implementation plans. Leverage strong analytical, statistical, and communication skills to assess complex security and business problems, align technical and non‑technical stakeholders, and drive decisions to closure in support of Booz Allen Hamilton's critical enterprise infrastructure, go‑to‑market platforms, and mission operations.

The ideal candidate for our Enterprise Cybersecurity team is technically inclined, intellectually curious, and adaptable, with a strong cyber‑defense mindset. They thrive in a fast‑paced, dynamic environment and are continuous learners who actively seek to understand complex challenges, ask thoughtful questions, and look beyond the obvious to identify innovative and effective ways of working. They bring a security‑first perspective, analytical problem‑solving skills, and the curiosity and aptitude to continuously evolve as threats, technologies, and mission needs change. This position is located in McLean, VA.

• Design, build, and deploy custom AI/ML solutions for cybersecurity, including supervised and unsupervised detection models, anomaly and behavioral analytics, NLP on security text, retrieval‑augmented generation (RAG) pipelines, agentic workflows, and LLM‑assisted analyst tooling, and operationalize them end‑to‑end: data ingest, feature engineering, training/tuning, evaluation, deployment, monitoring, and retraining.

• Engineer scalable data pipelines over security telemetry, including logs, EDR, network, identity, cloud, and threat intel, to produce high‑quality, labeled, and feature‑rich datasets that power detection, triage, and hunting use cases.

• Apply rigorous experimentation, statistical analysis, and evaluation methods, including precision/recall, drift, calibration, A/B testing, and backtesting against historical incidents to validate model performance, reduce analyst burden, and quantify operational impact.

• Apply secure‑AI and MLSecOps engineering practices throughout the AI/ML lifecycle, including model and data protection, prompt and inference risk mitigation, evaluation against adversarial inputs, including evasion, poisoning, and prompt injection, and responsible AI controls.

• Integrate models and analytics into security tools and workflows, such as SIEM, SOAR, EDR, IAM, CSPM, extending detection logic, enrichment, and response playbooks with custom ML/LLM capabilities where commercial tooling falls short.

• Develop automation, scripting, and infrastructure‑as‑code (IaC) to enable repeatable, testable, and version‑controlled ML pipelines, model deployments, and security data integrations.

• Collaborate across engineering, platform, data, threat intelligence, and SOC operations teams to deliver end‑to‑end solutions, embed security and ML practices into DevSecOps and MLSecOps pipelines, and drive implementation through measurable operational outcomes.

Join us. The world can't wait.

• 5+ years of experience in data science, machine learning engineering, or applied AI

• 3+ years of experience leading cross‑functional ML or analytics initiatives, including cybersecurity or security operations

• Experience designing and implementing data science and AI/ML solutions over enterprise security telemetry spanning network, endpoint, application, identity, and cloud environments

• Experience developing, testing, and integrating ML and analytic capabilities across security tools and platforms using APIs, automation, and workflow orchestration

• Experience with software development in Python and SQL for security and AI/ML use cases, including production‑quality code, unit and integration testing, version control, and CI/CD

• Experience with the modern AI/ML stack, including at least 2 of the following: PyTorch or TensorFlow, scikit‑learn, Hugging Face, LangChain, LlamaIndex, vector databases such as pgvector, OpenSearch, Pinecone, or Milvus, or embedding‑based retrieval

• Experience operationalizing AI/ML systems, such as MLOps, including model versioning, experiment tracking, evaluation harnesses, drift and quality monitoring, and CI/CD for models, such as MLflow, Weights and Biases, SageMaker, Vertex AI, Azure ML, or Kubeflow

• Experience applying AI and machine learning to cybersecurity use cases such as threat and anomaly detection, behavioral analytics, alert triage and prioritization, threat hunting support, analyst copilots, and response automation with an impact on SOC outcomes

• Ability to obtain a Secret clearance

• Bachelor's degree

• Experience with programming or scripting languages used in security and automation environments, such as Python, Go, SQL, PowerShell, or Bash

• Experience designing, deploying, and maintaining enterprise‑scale security solutions for sensitive or regulated environments, such as FedRAMP, IL4/5, HIPAA, or PCI

• Experience designing and building agentic AI systems for security operations, including multi‑step reasoning, tool and function calling, retrieval pipelines, and human‑in‑the‑loop workflows

• Experience fine‑tuning, distilling, or evaluating LLMs and other models for domain‑specific security tasks, including building eval datasets and red‑testing AI systems

• Experience evaluating and integrating AI‑enabled cybersecurity tooling, such as AI‑assisted SIEM/SOAR, UEBA, behavioral analytics, and model‑driven detection workflows into enterprise security operations

• Knowledge of AI governance, model risk management, and policy controls aligned to enterprise and regulatory expectations for responsible AI use

• Knowledge of data governance frameworks, data classification standards, and privacy regulations, such as GDPR, or CCPA

• Knowledge of database structures, data modeling fundamentals, and query optimization, including SQL and NoSQL platforms

• IT Engineering or Security Certifications, such as CISSP, CCSP, CDPSE, cloud security certifications, or relevant AI security certifications such as ISC2 CAISS or IAPP AIGP

Applicants selected will be subject to a security investigation and may need to meet eligibility requirements for access to classified information.

At Booz Allen, we celebrate your contributions, provide you with opportunities and choices, and support your total well‑being. Our offerings include health, life, disability, financial, and retirement benefits, as well as paid leave, professional development, tuition assistance, work‑life programs, and dependent care. Our recognition awards program acknowledges employees for exceptional performance and superior demonstration of our values. Full‑time and part‑time employees working at least 20 hours a week on a regular basis are eligible to participate in Booz Allen's benefit programs. Individuals that do not meet the threshold are only eligible for select offerings, not inclusive of health benefits. We encourage you to learn more about our total benefits by visiting the Resource page on our Careers site and reviewing Our Employee Benefits page.

Salary at Booz Allen is determined by various factors, including but not limited to location, the individual's particular combination of education, knowledge, skills, competencies, and experience, as well as contract‑specific affordability and organizational requirements. The projected compensation range for this position is $77,600.00 to $176,000.00 (annualized USD). The estimate displayed represents the typical salary range for this position and is just one component of Booz Allen's total compensation package for employees. This posting will close within 90 days from the Posting Date.

All qualified applicants will receive consideration for employment without regard to disability, status as a protected veteran or any other status protected by applicable federal, state, local, or international law.