Devise strategies for extracting meaning and value from large datasets, make and communicate principled conclusions from data, and translate mission needs into technical requirements.
Requirements
- 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
Responsibilities
- 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)
- 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 other 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 customer data holdings
- Translate practical mission needs and analytic questions related to large datasets into technical requirements and, conversely, assist other 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 constantly shifting collection, processing, storage and analytic capabilities and limitations
Other
- US Citizens Only
- Active TS/SCI Clearance and Polygraph required
- Information Assurance Certification may be required
- Minimum of ten (10) years of relevant experience and a Bachelor’s degree or twelve (12) years of relevant experience and an Associate’s degree required.
- A broader range of degrees will be considered if accompanied by a Certificate in Data Science from an accredited college/university
