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

@ Spry Methods
Spry Methodssprymethods.com

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

Posted 2 weeks ago

About the job

Spry Methods provides tech, cybersecurity, and program management for federal and DoD missions, focusing on cyber operations, data analytics, and innovative solutions in high-security environments.

Requirements

  • Active TS/SCI clearance with Polygraph
  • 8+ years supporting data science/cyber programs
  • 3+ years in cyber operations environments
  • 3+ years in machine learning and modeling
  • Proficiency in Python or R

Qualifications

  • Bachelor's in CS, Data Science, or related
  • Experience validating analytic models
  • Knowledge of SQL or similar tools
  • Ability to work in team environments
  • Strong problem-solving skills

Full job description

About Us:

Spry Methods is a proven provider of mission-focused technology, cybersecurity, and program management solutions supporting critical Federal and DoD missions. We specialize in delivering integrated, high-impact solutions across cyber operations, enterprise resource management, and mission support services. Our culture emphasizes collaboration, accountability, and innovation - empowering our teams to deliver meaningful outcomes in complex, high-security environments.

This position is tied to a federal proposal effort. Employment is contingent upon contract award and successful completion of the customer's onboarding and security requirements. Start dates and final reporting instructions will be confirmed upon award.

Who We’re Looking For (Position Overview):

Spry Methods is seeking an AI/ML Data Scientist to support Defensive Cyber Operations within a mission-focused environment. This role directly supports national security objectives by developing and deploying analytic capabilities that enable detection, analysis, and response to cyber threats.


The Data Scientist will work within an integrated team of engineers, analysts, and mission stakeholders to transform complex, high-volume data into actionable insights. The position emphasizes applied analytics, model deployment, and operational impact—moving beyond research to deliver solutions that support real-time cyber operations.



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


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