10 years of experience analyzing datasets and developing analytics.
10 years of programming experience in R, Python, SAS, or MATLAB.
Bachelor's degree in a quantitative field (statistics, mathematics, operations research, engineering, or computer science) plus 2 additional years of relevant experience, or a Bachelor's and Master's degree with no additional experience required.
PhD in a quantitative field can substitute for 4 years of experience, reducing the requirement to 6 years.
Strong understanding of security evaluation processes and risk management frameworks.
Responsibilities
Transform manual security evaluation processes into automated, efficient models.
Support continuous monitoring and rapid decision-making for critical systems.
Develop automated capabilities to enhance security evaluation and authorization.
Process and analyze security-related data using Python to ensure compliance with security requirements.
Detect anomalies and assess progress through the Risk Management Framework lifecycle.
Identify system associations based on various attributes and known information.
Design and maintain ETL pipelines for data integration from multiple sources.
Prepare data for reporting, analysis, and automated assessments.
Benefits
Opportunity to work on mission-driven projects that enhance security.
Collaborative team environment focused on innovation and efficiency.
Access to advanced tools and technologies for data analysis.
Professional development opportunities in data science and security fields.
Full Job Description
Responsibilities:
Data Scientist to join a mission driven team. In this role, you will help transform a traditionally manual system security evaluation process into an automated, efficient, and intelligence driven model.
Your work will directly support continuous monitoring, rapid decision making, and strengthened security across the full lifecycle of critical systems and projects
Develop and enhance automated capabilities that replace manual security evaluation and authorization processes.
Use Python to process, analyze, and validate security related data, ensuring systems and resources meet security requirements.
Detect anomalies and outliers to assess progress through the Risk Management Framework (RMF) lifecycle.
Identify system associations for resources based on various attributes and known system information.
Design, build, and maintain ETL pipelines to collect and integrate data from multiple sources (network sensors, security tools, compliance databases).
Transform and prepare data for reporting, analysis, and automated assessments.
Support data engineering operations including data quality checks, pipeline monitoring, workflow optimization, and timely delivery of security insights.
Enable scalable, reliable dataflows that support continuous monitoring and RMF automation.
Required:
10 years analyzing datasets and developing analytics
10 years programming in R, Python, SAS, or MATLAB
Education:
Bachelor's in a quantitative field (statistics, mathematics, operations research, engineering, or computer science) -Plus 2 additional years of relevant experience (12 years total) (software/cloud development, data analysis, or analytics development)
OR a Bachelor's and Master's degree (or higher) in a quantitative field (statistics, mathematics, operations research, engineering, or computer science) with no additional years of experience.
PhD can replace 4 years of the experience requirement (reducing to 6 years)
