Active TS.SCI clearance with Full-Scope Polygraph required.
Master's degree in a quantitative field or equivalent experience.
10 years of experience in dataset analysis and analytics development.
10 years of programming experience using R, Python, SAS, or MATLAB.
Background in statistical analysis with predictive modeling experience.
Responsibilities
Develop automated security evaluation processes for enterprise systems.
Leverage Python to analyze security data and system vulnerabilities.
Track systems' progress through the Risk Management Framework lifecycle.
Identify system affiliations through resource attribute analysis.
Design ETL pipelines to gather and process security data from multiple sources.
Ensure data quality and optimize workflows for timely security reporting.
Benefits
Opportunity to work on innovative security automation projects.
Flexible work environment with emphasis on continuous learning.
Access to cutting-edge tools and technology in cybersecurity.
Collaboration with seasoned professionals in a high-stakes environment.
Full Job Description
Description:
As part of the Secure the Enterprise initiative, 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 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.
Required:
Active and current TS.SCI w FSP through MD
Background in statistical analysis
Experience with building, tuning, and testing predictive models
Experience creating analytic charts and dashboards
Desired:
Elasticsearch
RegEx
Machine learning
Natural Language Processing
Regression and predictive analysis
Python
MATLAB or R
SQL or Mongodb
Metric Database (Grafana/Graphite/InfluxDB)
Education:
Master's degree from an accredited college or university in a quantitative discipline (e.g., statistics, mathematics, operations research, engineering or computer science).
Ten years of experience analyzing datasets and developing analytics, and ten years of experience programming with data analysis software such as R, Python, SAS, or MATLAB.
An additional two years of experience in software development, cloud development, analyzing datasets, or developing descriptive, predictive, and prescriptive analytics can be substituted for a Master's degree.
