Lead end-to-end data science workflows, including problem definition, data acquisition, feature engineering, model development, deployment, and lifecycle monitoring
Translate operational and training objectives into data-driven approaches and define analytical requirements for AI/ML integration into JTSE and Joint Training Tools
Design and maintain scalable data pipelines and architectures for real-time and near-real-time ingestion, processing, and analysis
Develop, train, and optimize machine learning models—including large-scale and foundation models—to enhance simulation and decision-support capabilities
Ensure data interoperability, quality, and consistency across multiple sources and systems
Integrate AI/ML models into simulation and synthetic environments, including FISE, to enable advanced analytics and scenario generation
Support exercise planning, execution, and after-action analysis using predictive analytics, anomaly detection, and performance metrics
Define and enforce data standards, schemas, and governance practices
Conduct model testing, validation, and performance evaluations
Identify and mitigate risks related to data quality, model bias, scalability, and performance
Support MLOps/DevSecOps practices for secure, reproducible, and continuous delivery
Collaborate with cross-functional government, industry, and mission partners
Document data pipelines, models, methodologies, and analytical findings for technical and non-technical audiences

5 years of related experience with a Bachelor’s degree
3 years with a Master’s
0 years with a PhD/JD
9 years of relevant experience with a high school diploma
Hands-on experience building and deploying machine learning or statistical models in operational environments
Strong knowledge of data processing, architectures, and distributed systems
Proficiency in Python or R and common data science libraries
Experience with data wrangling, feature engineering, and exploratory data analysis
Understanding of supervised/unsupervised learning and model evaluation
Experience creating technical documentation
Ability to work in cross-functional teams and manage multiple priorities
Strong analytical and problem solving skills
Experience working in Linux environments
Must have an active Secret Clearance

Data Scientist 3

Key skills