• Lead data science initiatives addressing complex intelligence integration, data exploitation, and cyberspace 
  mission analytics requirements. 
• Apply advanced statistical analysis, predictive modeling, entity resolution, graph analytics, explainable SI, and 
  operational analytics to identify patterns, relationships, anomalies, and trends across complex datasets.
• Develop, evaluate, and refine algorithms, machine learning models, analytical methods, and prototypes to 
  address mission-specific intelligence and operational problems.
• Analyze structured and unstructured data from multiple sources to assess data quality, relevance, utility, and 
  suitability for specific analytical and mission requirements.
• Design and implement data processing, transformation, parsing, tagging, and interconnection methods that 
  improve data usability, interoperability, and analytic readiness across heterogeneous data environments.
• Develop data triage methodologies and analytical workflows that optimize data prioritization, normalization, 
  enrichment, and integration across relevant intelligence domains.
• Evaluate data sources, formats, schemas, and structures to identify integration opportunities, resolve data 
  compatibility issues, and recommend approaches for improving data sharing and analytical performance.
• Develop and deploy data science applications, prototypes, proof-of-concept solutions, analytical tools, and 
  interactive visualizations that communicate complex findings and support mission decision-making.
• Implement reproducible analytical workflows using Python, PyTorch, Neo4j, Git, JIRA, and Streamlit, as 
  appropriate to the solution and mission requirements.
• Collaborate with software developers, data engineers, platform engineers, and other technical personnel to 
  integrate analytical models and applications into operational workflows and existing systems.
• Support the transition of selected analytical prototypes and models into production environments in coordination 
  with engineering and platform teams, including appropriate testing, documentation, version control, and 
  deployment practices.
• Identify opportunities to apply super intelligence, machine learning, automation, and advanced analytics to 
  improve intelligence processing, data exploitation, analytic efficiency, and operational effectiveness.
• Provide technical guidance and mentorship to other analysts and technical personnel, as appropriate, and 
  contribute to the development of analytical methodologies and best practices.
• Perform other related data science and technical support duties as assigned.

Required Qualifications:

Preferred Qualifications:

•         Generous cost sharing for medical insurance for the employee and dependents 
•         100% company paid dental insurance for employees and dependents 
•         100% company paid long-term and short-term disability insurance 
•         100% company paid vision insurance for employees and dependents 
•         401k plan with generous match and 100% immediate vesting 
•         Competitive Pay 
•         Generous paid leave and holiday package 
•         Tuition and training reimbursement 
•         Life and AD&D Insurance