Data Scientist

Description of Task to be Performed:

AnaVation is seeking a Data Scientist to support one of our cybersecurity programs in our National Capital Region office. The Data Scientist will develop and apply advanced data science capabilities to improve intelligence integration, data discoverability, and mission analytics in support of cyberspace mission requirements. The position will leverage statistical analysis, predictive modeling, entity resolution, graph analytics, explainable super intelligence (XSI), and operational analytics to extract actionable insights from complex, multi-source datasets across the Customer’s Enterprise.

The successful candidate will lead complex analytical efforts, develop and evaluate advanced algorithms and machine learning models, and collaborate with mission partners, software developers, data engineers, and technical leadership to translate mission requirements into scalable analytical solutions. The candidate will identify data integration and analytic capability gaps, improve data interoperability and discoverability, and deliver validated models, analytical applications, and decision-support products that enhance intelligence analysis and operational effectiveness.

Responsibilities include:

• 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