Support NSA/CSS data analysis efforts by applying advanced mathematical, statistical, and computational methods to derive mission-relevant insights.

Apply two or more skill areas across: Foundations (mathematical, computational, statistical), Data Processing (data management and curation, data description and visualization, workflow, reproducibility), Modeling, Inference, and Prediction (data modeling and assessment with domain-specific considerations).
Design approaches to extract meaning and value from large datasets.
Generate and communicate principled conclusions using mathematics, statistics, computer science, and application-specific knowledge.
Develop and implement qualitative and quantitative methods to characterize, explore, and assess large datasets across different conditions of organization, cleanliness, and structure, accounting for constraints unique to NSA/CSS data holdings.
Convert practical mission needs and analytic questions into technical requirements; also help stakeholders draw appropriate conclusions from analysis results.
Communicate complex technical findings to non-technical audiences.
Provide informed recommendations across competing technical solutions while tracking evolving NSA/CSS collection, processing, storage, and analytic capabilities and limitations.

Minimum experience: 10 years.
Education: Bachelor’s degree in Mathematics, Applied Mathematics / Statistics, Applied Statistics, Machine Learning, Data Science, Operations Research, or Computer Science, or related field (Computer Information Systems, Engineering), or a physical/hard sciences degree (e.g., physics, chemistry, biology, astronomy), or other science disciplines with substantial computational component with relevant coursework.
Additional education pathway: a broader range of degrees may be considered when accompanied by a Certificate in Data Science from an accredited college/university.
Relevant experience must include designing/implementing work such as: machine learning, data science, advanced analytical algorithms, and programming (including skill in at least one high-level language such as Python).
Relevant experience also includes: statistical analysis (variability, sampling error, inference, hypothesis testing, EDA, application of linear models), data management (cleaning and transformation), data mining, data modeling and assessment, artificial intelligence, and/or software engineering.

Data Scientist Level 3

Job Description