Design and deploy AI-enabled data solutions and machine learning pipelines for the DoD's CDAO ADA IR program. This role combines data science expertise with software engineering rigor to transform raw defense data into mission-critical decision-support tools.
Mission
This position supports the Department of Defense's Chief Data and Artificial Intelligence Officer (CDAO) Advanced Data Analytics Insights and Recommendations (ADA IR) program, serving Combatant Commands with advanced analytics and machine learning capabilities in mission-critical environments.
About this role
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 #: 1756
Job Title: Data Engineer - CDAO Central
Location: On-Site, Washington, D.C.
Clearance Level: Top Secret / 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
Typically has a Bachelor's degree in Computer Science, Information Systems, Data Engineering, or a related field (masters degree preferred)., and 3+ years of experience in data engineering or software engineering, with demonstrated experience in designing and managing complex data pipelines., or equivalent relevant work experience; e.g., each year of work experience may be substituted for each year of education required.
Years of Experience
3+ years
Required Skills
- Experience with data visualization and storytelling using tools such as Palantir's MSS Workshop and Slate applications
Preferred Skills
- 4+ years of experience in applied data science, Palantir Foundry development, 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).
- Familiarity with MLOps, API development, and secure cloud-based environments (e.g., AWS, Azure, Palantir Foundry).
- Strong understanding of data validation, model testing, and performance evaluation techniques.
- Excellent technical communication skills, with the ability to explain complex concepts to non-technical audiences.
Working Conditions
Must be able to work onsite at a SCIF
Required skills
- Data visualization and storytelling with Palantir MSS Workshop and Slate
- Data pipeline design and management
- Python programming
- SQL
- Machine learning model development
- Statistical modeling
- Software engineering practices
- Agile methodologies
- Secure containerized environments
- Technical communication