Data Scientist - AI/ML Specialist

CACI International•Fairfax, VA

2d•$94,400 - $198,200•Onsite

About The Position

CACI is seeking a Data Scientist to support the Department of Homeland Security’s Cyber Crimes Center (C3) by developing advanced AI and machine learning solutions for law enforcement investigations. The role designs and deploys production-grade AI/ML systems to help investigators combat cybercrime and dismantle criminal networks, working with a collaborative technical team to meet rigorous federal compliance standards. It applies machine learning to complex investigative challenges and supports responsible AI practices for national security operations. The position requires onsite work in Fairfax, Virginia, and travel of up to 25% within the Continental United States.

Requirements

Bachelor’s degree in Data Science, Computer Science, Artificial Intelligence, Statistics, Mathematics, Engineering, or a related technical field.
At least 5 years of demonstrated professional experience in a Data Science role.
At least 2 years of professional AI/ML experience, with a track record of delivering production AI systems.
Advanced proficiency with machine learning frameworks such as TensorFlow, PyTorch, and scikit-learn, and deep learning architectures.
Expert-level Python programming and extensive experience with Pandas, NumPy, and Spark.
Demonstrated experience deploying and maintaining production AI systems at scale.
Experience with on-premise infrastructure, data centers, and physical server environments.
Deep knowledge of explainable AI techniques and model interpretability methods such as SHAP and LIME.
Proven experience developing AI systems that comply with federal governance and ethical standards.
Proficiency with MLOps practices, model versioning, CI/CD pipelines, and workflow orchestration.
Willingness and ability to work onsite in Fairfax, Virginia.
Active Public Trust clearance or ability to obtain and maintain clearance.

Nice To Haves

Master’s degree or PhD in a related technical field.
Strong communication skills and ability to convey complex technical concepts to diverse audiences.
Experience with Generative AI, large language models, prompt engineering, and fine-tuning techniques.
Knowledge of AI security, bias detection and mitigation, and adversarial machine learning.
Background in federal law enforcement or intelligence community AI applications.
Expertise in Open-Source Intelligence (OSINT) analysis and cyber threat intelligence.
Proficiency with Elasticsearch, Kibana, graph databases, and investigative analytics platforms.
Familiarity with federal AI policies, including Executive Orders 13960 and 14110 and OMB guidance.

Responsibilities

Design and implement production AI/ML systems compliant with federal, DHS, and ICE governance requirements.
Develop explainable and auditable AI solutions with human-in-the-loop oversight mechanisms.
Build machine learning models for investigative analytics, including entity resolution, network analysis, and anomaly detection.
Develop scalable data pipelines and ETL processes using Apache Airflow, Spark, and on-premise infrastructure.
Design database solutions optimized for AI training, fine-tuning, and real-time inference on investigative data.
Implement continuous monitoring to detect bias, performance degradation, and security vulnerabilities.
Support AI Use Case approval processes, Security Authorization (ATO), and risk management protocols.
Document system architecture, data flows, and model explanations for audit and transparency requirements.
Integrate AI capabilities with existing investigative systems through APIs and microservices.
Ensure data provenance documentation and lawful data acquisition per federal requirements.
Collaborate with software engineers, infrastructure architects, and cybersecurity specialists on cross-functional projects.
Communicate technical concepts and model decisions to technical and non-technical stakeholders.
Maintain compliance with the AI Security Control Baseline and federal governance frameworks.
Contribute technical expertise to team initiatives and share knowledge and best practices with team members.