Data Scientist
About Agile Defense
Agile Defense knows that action defines the outcome and new challenges require new solutions. They aim to bring adaptive innovation to support critical missions through the integration of advanced technologies, elite minds, and unparalleled agility.
Requisition #: 1590
Job Title: Data Scientist
Location: In Person: Falls Church, VA | Ft. Meade, MD | Stuttgart, Baden-Württemberg, Germany | Tampa, FL | Honolulu (Camp H.M. Smith), HI | Colorado Springs, CO | Doral (Miami area), FL | Omaha (Offutt Air Force Base), NE | Scott Air Force Base, IL
Clearance Level: Top Secret with the ability to obtain an SCI, Must Have Clearance to Start
Job Description
Agile Defense seeks 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 involves 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.
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)
- 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
- Experience with data visualization and storytelling using tools such as Tableau, Plotly, or Matplotlib
- Excellent technical communication skills, with the ability to explain complex concepts to non-technical audiences
Preferred Skills
- Experience developing ML models from training to deployment using industry-standard tools and libraries (e.g., scikit-learn, TensorFlow, XGBoost, MLflow)
- Familiarity with MLOps, API development, and secure cloud-based environments (e.g., AWS, Azure, Palantir Foundry)
- Experience with data visualization and storytelling using tools such as Tableau, Plotly, or Matplotlib
- Experience with cloud-based data platforms such as Databricks, Palantir, or AWS-native data services
Our Core Values
- Happy - Be Infectious
- Helpful - Be Supportive
- Honest - Be Trustworthy
- Humble - Be Grounded
- Hungry - Be Eager
- Hustle - Be Driven