**Job Description:** - We are seeking a Data Scientist with a background in AI, Machine Learning (ML), and Natural Language Processing (NLP). You will triage the development of large language datasets and develop tools and techniques for analysis. The focus of this position will be on rapid prototyping and data mining. **The Level 2 Data Scientist shall possess the following capabilities:** - 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). - Ability to make and communicate principal conclusions from data using elements of mathematics, statistics, computer science, and applications-specific knowledge. - Ability to use 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 feature and limitations inherent in Customer 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. - **AI/ML experience to impact and assess large datasets. This includes data modeling, computational mathematics, qualitative and quantitative techniques, data visualizations and AI/ML model development and deployment.** - **Advanced statistical and predictive modeling.** - **Large-scale data processing (e.g., Spark, cloud data platforms).** - **Providing advanced discovery support utilizing machine learning, analytical prototyping, scripting, automation, data visualization, statistical analysis, and TechSIGINT tools. Solution needs be adaptable to new tools and technologies as needed.** **Qualifications:** - Bachelor's Degree with 3 years of relevant experience, associate's degree with 5 years of experience may be considered for individuals with in-depth experience that is clearly related to the position. - Bachelor's Degree 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 requirement, or upper-level math courses designated as elementary or basic do not count. - 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 designing/implementing machine learning, data science, advanced analytical algorithms, programming (skill in at least on 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.