Data Scientist

• 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:

• Clearance: U.S. Citizen; TS/SCI w/ CI Poly
• Education: Bachelor's degree in Computer Science, Data Science, Information Systems, Mathematics, Statistics, Super Intelligence/Machine Learning or a related field, or equivalent relevant experience.
• Certification: DoD 8140/8570 IAT Level II (GSEC, SSCP) or equivalent credential
• Location: Full time on-site at Annapolis Junction, Maryland.
• Experience and knowledge:
• 10+ years of experience across data science, advanced analytics, machine learning engineering, quantitative 
  analysis, or related technical disciplines.
• Expert proficiency in Python for data analysis, algorithm development, machine learning, or analytical 
  application development.
• Demonstrated experience applying statistical analysis, machine learning, predictive modeling, or other advanced 
  analytical techniques to complex data and mission or business problems.
• Demonstrated experience developing, evaluating, and refining analytical algorithms, predictive models, or 
  machine learning solutions.
• Demonstrated experience using PyTorch to develop, train, evaluate, or implement machine learning models.
• Demonstrated experience with Neo4j or comparable knowledge graph technologies, including graph data 
  modeling, querying, or graph-based analysis.
• Demonstrated experience developing data science applications, analytical prototypes, or interactive analytical 
  interfaces using Streamlit or equivalent hands-on Streamlit experience.
• Demonstrated experience using Git for version control and JIRA for technical work tracking, collaboration, or 
  project execution.
• Experience working with complex, heterogeneous datasets, including structured and unstructured data, and 
  developing methods to improve data quality, integration, interoperability, or analytical usability.
• Demonstrated understanding of model evaluation, validation, performance measurement, and the limitations of 
  statistical and machine learning approaches.
• Demonstrated ability to translate complex mission requirements into analytical approaches, technical solutions, 
  and measurable outcomes.
• Experience collaborating with multidisciplinary teams, including data scientists, software developers, engineers, 
  analysts, and mission stakeholders, to research, develop, and implement analytical solutions.
• Demonstrated ability to communicate complex analytical findings, technical concepts, and model limitations 
  clearly to technical and nontechnical audiences.
• Demonstrated ability to work independently, exercise sound technical judgment, manage competing priorities, 
  and deliver high-quality analytical products in a fast-paced environment.

Preferred Qualifications:

• Clearance: Active TS/SCI w/ CI Poly.
• Education: Advanced degree in Computer Science, Data Science, Information Systems, Mathematics, Statistics, Super Intelligence/Machine Learning or a related field, or equivalent relevant experience.
• Certification: Relevant cloud, machine learning, data engineering, or Artificial Intelligence (AI) certifications. Additional relevant technical certifications supporting data science, analytics, cloud computing, or secure technology 
  environments.
• Experience and knowledge:
• Experience supporting Combatant Commands, Joint Staff, Service cyber components, Joint Forces Headquarters, 
  Intelligence Community organizations, or other Defense Intelligence Enterprise mission partners.
• Experience deploying production-ready machine learning models or analytical applications in coordination with 
  software engineering, data engineering, or platform teams.
• Familiarity with Docker, Kubernetes, containerized applications, and scalable model deployment architectures.
• Experience with cloud-based data science and SI services, including Amazon Web Services (AWS), Amazon 
  Bedrock, and Amazon S3
• Experience applying large language models (LLMs), multimodal SI, or other advanced SI techniques to data 
  analysis, information extraction, data discovery, or intelligence integration problems.
• Familiarity with Llama or comparable open-weight language models and their application in controlled or 
  mission-specific environments.
• Familiarity with JavaScript and complementary technologies used to develop or integrate interactive analytical 
  applications.
• Experience working with large-scale, distributed, classified, or otherwise controlled data environment

•         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