Data Scientist II
1 week ago
DUTIES As a successful candidate for the Data Scientist III role, you will develop strategies to extract insights from large datasets using mathematics, statistics, computer science, and domain knowledge. Apply analytic modeling, statistical analysis, and programming to explore and assess complex datasets across varying formats and quality. Translate mission needs into technical requirements, guide analysis, and communicate findings clearly to non-technical audiences. Make informed recommendations by staying current with NSA/CSS data capabilities and limitations. Developing data analytics and automating analytic workflows.
Required Skills
SKILLS Employ some combination (2 or more) of the following skill areas:
- Foundations: (Mathematical, Computational, Statistical)
- Data Processing: (Data management and curation, data description and visualization, workflow and reproducibility)
- Modeling, Inference, and Prediction: (Data modeling and assessment, domain-specific considerations)
QUALIFICATIONS
You must have:
- Data Parsing Tool knowledge
- Data flow knowledge
- Python experience
Bachelor'sDegree must be in Mathematics, Applied Mathematics, Statistics, Applied Statistics, Machine Learning, Data Science, Operations Research, or Computer Science or a degree in a related field (Computer Information Systems, Engineering), a degree in the physical/hard sciences (e.g. physics, chemistry, biology, astronomy), or other science disciplines with a substantial computational component (i.e. behavioral, social, or life) may be considered if it included a concentration of coursework (5 or more courses) in advanced Mathematics (typically 300 level or higher, such as linear algebra, probability and statistics, machine learning) and/or computer science (e.g. algorithms, programming, data structures, data mining, artificial intelligence).
College-level requirements, or upper-level math courses designated as elementary or basic, do not count. A broader range of degrees will be considered if accompanied by a Certificate in Data Science from an accredited college/university.
Relevant experience must be in one or more of the following areas:
- Designing/implementing machine learning
- Data science
- Advanced analytical algorithms
- Programming (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
- Software engineering
Experience in more than one area is strongly preferred.
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