Job Description

ACTIVE SECURITY CLEARANCE AT THE TS/SCI POLYGRAPH LEVEL IS REQUIRED

In this mission-critical role, you will sit at the crossroads of data science, data engineering, and automated compliance. You will leverage Python to process, analyze, and validate complex security datasets, deploying statistical models and anomaly detection algorithms to spot outliers as systems progress through the Risk Management Framework (RMF) lifecycle. Beyond analytical modeling, you'll roll up your sleeves to build and maintain robust ETL pipelines-integrating raw data from network sensors, security tools, and compliance databases into clean, actionable intelligence streams. If you love solving messy data challenges, building scalable dataflows, and bringing your authentic self to secure critical national systems, Team Nyla wants you on our team!

The annual base salary range for this role is $190,000-$225,000 (USD) , which does not include discretionary bonus compensation or our comprehensive benefits package. Actual compensation offered to the successful candidate may vary from posted hiring range based upon geographic location, work experience, education, and/or skill level, among other things.

Required Skills

• Python Analytics & Data Processing: Demonstrated proficiency using Python to extract, manipulate, analyze, and validate complex datasets for automated decision-making.
• Anomaly Detection & Statistical Analysis: Hands-on experience developing algorithms to identify outliers, detect anomalies, and track system progress across multi-attribute data environments.
• ETL & Data Pipeline Engineering: Proven experience designing, building, and maintaining scalable ETL pipelines to collect, transform, and integrate data from disparate sources (e.g., network sensors, security tools, databases).
• RMF & System Security Context: Practical understanding of security evaluation processes, system association mapping, and Risk Management Framework (RMF) continuous monitoring requirements.
• Data Engineering Operations: Capability to ensure data reliability through automated quality checks, workflow optimization, and continuous pipeline monitoring.

Education: Bachelor's Degree in Data Analytics, Intelligence Studies, Computer Science, Finance/Economics, or a related discipline, PLUS 8+ years of specialized data analytics or financial intelligence experience OR High School Diploma / GED, PLUS 13+ years of hands-on intelligence analysis, financial tracking, and data discovery experience in lieu of a degree.

Desired Skills

Experience integrating data science models directly into cloud environments (e.g., AWS, automated security evaluation frameworks).

Familiarity with database architectures (SQL/NoSQL) and modern visualization dashboards for presenting continuous monitoring insights.

Excellent technical communication skills with an appetite for automating away legacy manual workflows.