Data Scientist

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 #: 1424

Data Scientist / Engineer

Top Secret clearance

Alexandria, VA | Arlington, VA

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 and Joint Staff.

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.

Location:

Remote | Falls Church, VA | Arlington, VA | DC Metro

Clearance:
Active DoD Secret (or ability to obtain)

Citizenship: U.S. Citizenship required

• Plan, develop, and maintain reusable services for data ingestion, transformation, and feature engineering that support AI/ML workflows.
• Implement core data science capabilities, such as entity resolution, classification, clustering, or prediction, within containerized environments that adhere to CI/CD, version control, and testing standards.
• Collaborate with Dev Sec Ops  engineers to integrate services into secure production environments using tools like Databricks, Docker, and Terraform.
• Ensure services meet performance, reliability, and security requirements consistent with DoD enterprise and cloud-native architecture.

• Develop and deploy standalone or embedded ML models for tasks such as decision support, automation, anomaly detection, and pattern recognition.
• Select and implement appropriate modeling techniques using Python, Spark, or cloud-native ML frameworks (e.g., Sage Maker, MLflow).
• Maintain reproducibility and interpretability of model outputs to meet mission transparency and audit requirements.
• Package model inference services with well-documented APIs for integration into end-user applications and operational dashboards.

• Conduct exploratory data analysis (EDA) to identify trends, gaps, and opportunities within structured and unstructured datasets.
• Develop data visualizations and interpretive summaries that support stakeholder understanding and product team decision‑making.
• Translate analytical findings into actionable recommendations using a mix of visual, narrative, and quantitative communication strategies.
• Contribute to the team’s shared library of analysis templates, reusable queries, and analytic workflows to accelerate future delivery.

• Engage with product managers and mission users to define data and model requirements aligned with operational goals.
• Work closely with engineers to ensure data science components align with technical…