Data Processing: (Data management and curation, data description and visualization, workflow and reproducibility).
Modeling, Inference, and Prediction: (Data modeling and assessment, domain-specific considerations).
Agentic AI
RAG
skill in at least one high-level language e.g. Python
statistical analysis (e.g. variability, sampling error, inference, hypothesis testing, EDA, application of linear models), data management (e.g. data cleaning and transformation), data mining, data modeling and assessment, artificial intelligence, and/or software engineering.
Responsibilities
Devise strategies for extracting meaning and value from large datasets.
Make and communicate principled conclusions from data using elements of mathematics, statistics, computer science, and application specific knowledge.
Through analytic modeling, statistical analysis, programming, and/or another appropriate scientific method, develop and implement qualitative and quantitative methods for characterizing, exploring, and assessing large datasets in various states of organization, cleanliness, and structure that account for the unique features and limitations inherent in DOD data holdings.
Translate practical mission needs and analytic questions related to large datasets into technical requirements and, conversely, assist others with drawing appropriate conclusions from the analysis of such data.
Make informed recommendations regarding competing technical solutions by maintaining awareness of the constantly shifting DOD collection, processing, storage and analytic capabilities and limitations.
Familiarity with AI/ML model development and deployment.
Machine Learning model training
Other
Bachelor's Degree with 10 years of relevant experience.
Associates degree with 12 years of relevant experience.
Effectively communicate complex technical information to non-technical audiences.
