Data Scientist - Mid Level active TS/SCI in Caseyville

This interesting work requires staff qualified to have a basic understanding of GEOINT integration work but also act as a Data Scientist for NGA. The work requires a basic understanding of GEOINT from collection, exploitation, analysis and product delivery capabilities.

3-6 years’ experience in programming such as Python or R (statistical analysis), data preprocessing, and basic machine learning algorithms.

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• \n Provide data management and automation support to a specialized imagery and geospatial analysis division within a government or enterprise organization. \n

• \n Assist with developing a modernized data management workflow supporting multiple organizational programs. \n

• \n Collaborate with senior data scientists, database developers, and analysts to implement and sustain updated database processes and workflows. \n

• \n Research and document existing data management practices, procedures, and system dependencies. \n

• \n Help design improved workflows with automation incorporated from the outset. \n

• \n Ensure new workflows integrate effectively with modern database applications and enterprise-level application programming interfaces. \n

• \n Enhance existing models and simulations involving production, monitoring, and change-detection data. \n

• \n Support additional data management and modernization initiatives as required. \n

• \n Develop code and scripts, including the conversion of legacy applications written in multiple programming into Python-based solutions. \n

• \n Implement enterprise database management standards, processes, and controls. \n

• \n Automate repetitive data preparation, validation, transformation, and reporting tasks. \n

• \n Deliver technical solutions that apply industry best practices to modernize existing operational processes. \n

• \n Conduct data investigations using applied statistics, algorithm development, and collaboration with subject-matter experts. \n

• \n Translate complex analytical findings and operational realities into clear explanations for non-technical audiences. \n

• \n Create visualizations and dashboards from diverse data sources that are accessible and understandable to non-technical users. \n

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