Data Scientist 2 with Security Clearance

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Job description

We're searching for talented individuals who provide intelligence, statistical analysis and programming expertise for the Government. This program will maximize the effectiveness and efficiency of our country's most important missions both at home and abroad. If you are ready to support a high-performing team that truly makes a difference, then come join us! Job Description: We are looking for a Data Scientist skilled in Python and Jupyter Notebooks to develop and maintain data-driven solutions. In this role, you'll analyze complex datasets, build models, and create interactive tools that support decision-making and operational efficiency across the organization. The Level 2 Data Scientist shall possess the following capabilities: 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) 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. 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 organization, cleanliness, and structure that account for the unique features and limitations inherent in Government 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 Government collection, processing, storage and analytic capabilities and limitations. Qualifications: Bachelor's Degree with 3 years of relevant experience Associates degree with 5 years of relevant experience 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. Note: 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 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 oflinear models), data management (e.g. data cleaning and transformation), data mining, data modeling and assessment, artificial intelligence, and/or software engineering. Experience in more than one area is strongly preferred. Position requires active Security Clearance with appropriate Polygraph Application Window:
While subject to change based on business needs, RealmOne reasonably anticipates that this job requisition will remain open for at least 3 days with an anticipated close date of no earlier than 3 days after the original posting date as listed above.

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