Data Scientist

About Agile Defense   At Agile Defense we know that action defines the outcome and new challenges require new solutions. That’s why we always look to the future and embrace change with an unmovable spirit and the courage to build for what comes next.   Our vision is to bring adaptive innovation to support our nation's most important missions through the seamless integration of advanced technologies, elite minds, and unparalleled agility—leveraging a foundation of speed, flexibility, and ingenuity to strengthen and protect our nation’s vital interests.
Requisition #: 1627 Job Title: Data Scientist Location: Washington, D.C. Clearance Level: Top Secret with the ability to obtain an SCI, Must Have Clearance to Start    

Job Description

Agile Defense is seeking a Data Scientist / Engineer to support the design, development, and operational deployment of scalable, AI-enabled data solutions within the Department of Defense’s CDAO ADA IR program. This role is part of a multidisciplinary team integrating advanced analytics, machine learning, and engineering practices into mission-critical environments at Combatant Commands.
You will help shape and deploy data pipelines, pre-processing workflows, feature engineering strategies, and machine learning services within secure, containerized environments. The ideal candidate brings a hybrid of statistical modeling fluency and hands-on software engineering expertise. You will collaborate closely with product managers, full-stack developers, platform engineers, and mission stakeholders to transform raw data into meaningful insights and decision-support tools.
This role requires strong technical communication skills, a collaborative mindset, and experience working in agile environments that value reproducibility, testing, and continuous delivery. Familiarity with cloud-based data platforms such as Databricks, Palantir, or AWS-native data services is highly preferred.

Education and Background

• A bachelor's degree plus 3 years of recent specialized experience, OR, an associate's degree plus 7 years of recent specialized experience, OR, a major certification plus 7 years of recent specialized experience, OR, 11 years of recent specialized experience

Years of Experience

Depends on educational background and years of work experience.

Required Skills

• 4+ years of experience in applied data science, machine learning engineering, or data pipeline development.
• Proficient in Python, SQL, and distributed data frameworks (e.g., Spark, Databricks, PySpark).
• Experience developing ML models from training to deployment using industry-standard tools and libraries (e.g., scikit-learn, TensorFlow, XGBoost, MLflow).