Data Scientist III

Reflexive ConceptsLinthicum, MD

About The Position

As part of the Secure the Enterprise initiative, Reflexive Concepts is seeking a skilled Data Scientist III to 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 monitoring and assessment, and network data gathering across the entire life cycle of a project. This role 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, and identify which system a resource belongs to, determined by various attributes of the identified resource against known potential system information. The position also involves designing, developing, and maintaining ETL pipelines to extract security and compliance data from multiple sources, transforming the data for analysis and reporting, and loading it into target data repositories to support continuous monitoring and automated assessments. Additionally, the role will 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.

Requirements

  • Twenty-two (22) years of experience supporting projects and programs similar in scope and complexity
  • Bachelors Degree in a related field
  • Background in statistical analysis
  • Experience with building, tuning, and testing predictive models
  • Experience creating analytic charts and dashboards

Nice To Haves

  • Elasticsearch
  • RegEx
  • Machine learning
  • Natural Language Processing
  • Regression and predictive analysis
  • Python
  • MATLAB or R
  • SQL or MongoDB
  • Metric database (Grafana/Graphite/InfluxDB)

Responsibilities

  • 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 monitoring and assessment, and network data gathering across the entire life cycle of a project.
  • 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, determined by various attributes of the identified 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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