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 applicationspecific 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 organimtion, cleanliness, and structure that account for the unique features and limitations inherent in Agency 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. Effectively communicate complex technical information to non-technical audiences. Make informed recommendations regarding competing technical solutions by maintaining awareness of the constantly-shifting Agency collection, processing, storage and analytic capabilities and limitations.
Capabilities
- Foundations (Mathematical, Computational, Statistical)
- Data Processing (Data management and curation, data description and visualization, workflow and reproductibility)
- Modeling, Inference, and Prediction (Data modeling and assessment, domain-specific considerations)
- 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
- Make and communicate principled conclusions from data using elements of mathematics, statistics, computer science, and application specific knowledge
- 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
- Effectively communicate complex technical information to non-technical audiences
- Make informed recommendations regarding competing technical solutions by maintaining awareness of the constantly-shifting NSA/CSS collection, processing, storage and analytic capabilities and limitations
- TS/SCI with Agency Appropriate Polygraph
- A Bachelor’s degree and 10 years of relevant experience. An Associate’s degree plus 12 years of relevant experience may be considered for individuals with in-depth experience that is clearly related to the position
- Degree must be in Mathematics, Applied Mathematics, Statistics, Applied Statistics, Machine Learning, Data Science, Operations Research, or Computer Science. A degree in a related field (e.g., 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, and life) may be considered if it includes a concentration of coursework (typically 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., algorthms, programming, data structures, data mining, artificial intelligence). College-level Algebra or other math courses intended to meet a basic college level requirement, 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
- TSR focused Data Science requirement – prefer knowledge of working with Big Data, dataflows, ML/AI familiarity, analytics in GME and Jupyter notebooks and Spark
Wyetech, LLC is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, or protected veteran status and will not be discriminated against on the basis of disability.
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