The Data Scientist will develop capabilities to shift from the current manual system security evaluation and authorization process to a new model that emphasizes automation, streamlined processes and approvals, continuous assessment and network data gathering across the entire lifecycle of a project. They will leverage Python as a primary language to process data to accurately determine if resources and systems are secure. Look for outliers to help track the progress of systems through the Risk Management Framework lifecycle. Identify which System a Resource belongs to be determined by various attributes of the identified lost Resource against known potential System information. Design, develop, and maintain ETL pipelines to extract security and compliance data from multiple sources (network sensors, security tools, compliance databases), transform the data for analysis and reporting, and load it into target data repositories to support continuous monitoring and automated assessments. Support data engineering operations including data quality validation, pipeline monitoring, and optimization of data workflows to ensure reliable, scalable, and timely delivery of security-related data for Risk Management Framework automation and decision-making.
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Job Type
Full-time
Career Level
Senior