Data Scientist - AI/ML (TS/SCI w/Poly)

What Your Day-To-Day Looks Like (Position Responsibilities):

Apply machine learning, statistical methods, and analytics to address cyber and intelligence-related challenges  

Design, develop, and optimize models for pattern detection, classification, and anomaly identification  

Ingest, transform, and integrate data from multiple sources to support analytic workflows  

Build and maintain data pipelines and ensure data quality, consistency, and accessibility  

Deploy analytic models into production and monitor performance for continuous improvement  

Collaborate with analysts and operators to interpret results and refine analytic approaches  

Translate technical findings into clear, actionable insights for stakeholders  

Support rapid prototyping and delivery of new analytic capabilities in operational environments  

Document data sources, models, and processes to ensure transparency and reproducibility  

Stay current with emerging data science techniques and tools to enhance mission impact 

What You Need to Succeed (Minimum Requirements):

• Active TS/SCI clearance with polygraph  

• Bachelor’s degree in Computer Science, Data Science, Mathematics, Engineering, or related field  

• 8+ years of experience supporting data science, analytics, or cyber-related programs (or equivalent combination of education and experience)  

• 3+ years of experience supporting Defensive Cyber Operations environments  

• 3+ years of hands-on experience with machine learning and statistical modeling  

• Experience evaluating, validating, and implementing analytic models in operational environments  

• Proficiency in one or more programming languages used for data analysis (e.g., Python, R)  

• Experience using SQL or similar tools to manipulate and analyze data 

Ideally, You Also Have (Preferred Qualifications):

Experience with:  

• Cloud environments (e.g., AWS) 

• Big data platforms and distributed data processing 

• Cybersecurity frameworks, controls, or compliance requirements (e.g., STIGs, IAVAs) 

• Strong technical background in:  

• Linux (e.g., Ubuntu, CentOS, RHEL) and/or Windows environments 

• Virtualized or hybrid infrastructure 

• Experience with:  

• Jupyter Notebooks and interactive data analysis tools 

• Network analysis and cyber data sets 

• Familiarity with:  

• Automation and scripting for analytic workflows 

• Software development practices and collaboration with engineering teams