Data Scientist

Core One develops analytical, operational, and technical solutions to complex national security challenges while emphasizing a people-first, team-oriented culture. The Data Scientist will conduct advanced data analytics, engineering, mining, statistical analysis, and Multi-INT analysis across complex datasets to support intelligence missions. The role will also develop machine learning models, data pipelines, visualizations, and analytical products for data-driven decision-making.

What you'll do:

• Conduct data analytics, data engineering, data mining, exploratory analysis, predictive analysis, and statistical analysis across large and complex datasets to support intelligence and mission requirements
• Collect, retrieve, integrate, and transform data from disparate sources to identify relationships, trends, patterns, and insights that support informed analytical and operational decision-making
• Apply scientific, statistical, and computational techniques to correlate and interpret data and produce graphical, written, visual, and verbal analytical products
• Design, develop, test, and implement machine learning (ML) models, artificial intelligence (AI) tools, and automated analytical processes to improve data processing, analysis, and mission workflows
• Develop ML-enabled applications and processes, including recommendation engines, automated lead-scoring systems, classification models, predictive models, and other automated decision-support capabilities
• Develop, train, evaluate, and optimize statistical and machine learning models to produce accurate, scalable, and reliable predictive analytics
• Apply data mining techniques and statistical methodologies to identify trends, correlations, anomalies, and predictive indicators within large and complex datasets
• Integrate and merge structured and unstructured data from multiple and disparate sources using R, Python, SQL, and other appropriate data engineering and analytical tools
• Develop and maintain data pipelines, analytical workflows, and automated processes to support the collection, transformation, analysis, and visualization of large datasets
• Conduct large-scale Multi-INT data analytics by integrating and analyzing data from multiple intelligence disciplines, sources, and formats to identify relationships, patterns, and actionable insights
• Apply machine learning and automated predictive analytics techniques to large datasets to support intelligence production, forecasting, pattern recognition, and identification of emerging trends
• Develop data visualizations, dashboards, charts, and graphical products using tools such as Microsoft Power BI and Tableau to communicate complex analytical findings to technical and non-technical audiences

What they're looking for:

• * Junior: Minimum of one year of experience conducting analysis relevant to this Labor Category
• * Mid: Minimum of three (3) years of experience conducting analysis relevant to this Labor Category
• * Senior: Minimum of eight (8) years of experience conducting analysis relevant to this Labor Category
• * Expert: Minimum of twelve (12) years of experience conducting analysis relevant to this Labor Category
• * Working knowledge of data science, data engineering, data analytics, data mining, statistical analysis, exploratory analysis, predictive analytics, and machine learning concepts applicable to intelligence and mission requirements
• * Experience applying data science and analytical techniques to large, complex, and disparate datasets to identify trends, patterns, correlations, anomalies, and actionable insights
• * Experience collecting, cleaning, transforming, integrating, and managing structured and unstructured data from multiple sources using technologies such as Python, R, SQL, and other appropriate data engineering tools
• * Experience developing, testing, evaluating, and implementing machine learning models, artificial intelligence tools, predictive analytics, and automated data-processing solutions
• * Experience applying statistical methods and data mining algorithms to develop predictive models, classification systems, recommendation engines, automated lead-scoring systems, and other ML-enabled analytical capabilities
• * Experience developing and optimizing data pipelines, analytical workflows, scripts, and automated processes to improve the efficiency, scalability, accuracy, and repeatability of data analysis
• * Experience conducting large-scale Multi-INT analytics by integrating and analyzing data from multiple intelligence disciplines, sources, systems, and formats
• * Experience evaluating the performance, accuracy, reliability, and applicability of statistical and machine learning models and refining models based on analytical results and validation