Design and deploy AI-enabled data solutions and machine learning pipelines supporting DoD CDAO ADA IR missions at TRANSCOM. This role blends data science rigor with software engineering to transform raw military intelligence into actionable decision-support tools.
What you'll do
- Design, develop, and operationalize scalable data pipelines and pre-processing workflows in secure, containerized DoD environments
- Build feature engineering strategies and machine learning services using Python, SQL, and distributed frameworks (Spark, Databricks)
- Develop and validate ML models from training through production deployment using industry-standard tools (scikit-learn, TensorFlow, XGBoost)
- Create data visualizations and storytelling outputs using Palantir MSS Workshop and Slate applications for mission stakeholders
- Collaborate with product managers, developers, platform engineers, and operational teams to translate raw data into meaningful insights and decision-support capabilities
- Implement MLOps practices, API development, and performance evaluation techniques to ensure reproducibility, testing, and continuous delivery
- Communicate complex technical concepts to non-technical audiences and mission partners in agile team settings
Mission
This position supports the Department of Defense's CDAO (Chief Data and Analytics Office) ADA IR program at U.S. Transportation Command (TRANSCOM). The work integrates advanced analytics and machine learning into mission-critical environments within Combatant Commands to enhance operational decision-making and mission effectiveness.
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 fundamentals
- Agile development practices
- Technical communication
- Secure containerized environments