Senior Data Scientist

Are you ready to join Leidos all-star team? Through training, teamwork, and exposure to challenging technical work, let Leidos show how to accelerate your career path. Leidos is seeking a mission-driven Senior Data Scientist to join our high-impact team supporting the National Digital Exploitation and Open Source Center (NDOC) DOMEX Technology Platform (DTP). In this role, you will help improve data intelligence pipelines serving both Open Source Intelligence (OSINT) operations and document media exploitation for the Department of War (DoW) and the broader Intelligence Community (IC). You’ll play a critical role in developing a future state AI-managed DOMEX Data Discovery Platform (D3P) and DIA-NDOC’s mission. As a key technical leader, you will collaborate with talented scientists, engineers, product owners, and government stakeholders to design, develop, and deploy innovative software solutions that make a real difference to national security. You will work closely with the team on the following key tasks As a Data Scientist, you will perform pattern analysis and discovery over large quantities of data maintained in various associative structures, developing dashboards to initiate discovery and present results. Working closely with data engineers, software engineers, and infrastructure teams, you will work with Elasticsearch and graph-based data platforms to discover and analyze complex data relationships. * Investigate and develop embedding space solutions for optimal search and discovery over structured datasets such as source code repositories, document references. * Investigate graph-structure analysis to discover complex network structures meta-paths and meta-structures over heterogenous graphs. * Design statistical approaches to handle near-duplicate data and uncertain relationships. * Support and respond to requests from a Government Data Science team to discover and report specific findings within graph representations of data including the construction of custom dashboards, optimizing search queries, and transforming provided datasets into canonical graph structures. * Support the design and optimization Elasticsearch indices to efficiently manage large-scale hierarchical classification structures, ensuring high-performance search, aggregation, and update operations. * Support data engineering in the design, implementation, and maintenance of a graph data store supporting hierarchical graph structures optimized for large, dense batch updates and high-throughput analytics.

• Prototype ingestion pipelines that support scalable graph analytics.
• Support data engineering in implementations of data schemas, indexing

strategies, and partitioning approaches to maximize query performance, scalability, and storage efficiency. * Collaborate with infrastructure and platform engineering teams to deploy, operate, and optimize Elasticsearch and graph database services in a Kubernetes environment using cloud-native technologies. * Partner with Data Scientists, Data Engineers and AI/ML Engineers to ingest, curate, manage, analyze, and securely expunge datasets throughout the data lifecycle. * Develop automated data loading, transformation, validation, and quality assurance pipelines supporting production analytics workflows. * Optimize graph and search infrastructure for high availability, resilience, and performance under large-scale analytical workloads. * Collaborate with software engineers and system architects to integrate graph and search services into microservice-based applications. * Participate in SAFe Agile development activities, including sprint planning, design reviews, architecture discussions, and technical demonstrations. * Foster a culture of innovation, collaboration, and professional development within the team. * Ensure sound engineering practices, compliance with policies, and delivery of high-quality software. * Coordinate with test teams to develop and monitor automated system integration tests. * Engage with cross-functional teams to identify and develop high-value integrations with other systems/applications. * Provide specific input to the software components of system design to include hardware/software trade-offs, software reuse, use of COTS/GOTS in place of new development, and requirements analysis and synthesis from system level to individual software components. To be successful in this role you need these skills (required): * Bachelor’s degree in Computer Science, Data Science, or related field and 8–12 years of relevant experience, or Master’s with 6–10 years of experience. * Must possess an Active Top Secret/SCI clearance and ability to obtain and maintain a Polygraph. * Elasticsearch/OpenSearch architecture, index design, mappings, analyzers, and query optimization. * Graph databases such as JanusGraph, Neo4j, TigerGraph, Amazon Neptune, or Memgraph. * Graph analytics frameworks and algorithms, including graph traversal, centrality, community detection, similarity analysis, and link prediction. * Experience training Neural Networks including data selection for train, evaluation and test. * Experience with constructing static and interactive visualizations and dashboards including link charts. * Proficient in Python. You will wow us even more if you have some of these skills: * Experience with Linux, containerization, CI/CD pipelines, and Infrastructure-as-Code.

• Familiar with Graph Neural Networks including GCN and GTNs.
• Experience with Anomaly Detection models.

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ORIGINAL POSTING:

July 27, 2026 For U.S. Positions: While subject to change based on business needs, Leidos reasonably anticipates that this job requisition will remain open for at least 3 days with an anticipated close date of no earlier than 3 days after the original posting date as listed above.

PAY RANGE:

Pay Range $107,900.00 - $195,050.00 The Leidos pay range for this job level is a general guideline only and not a guarantee of compensation or salary. Additional factors considered in extending an offer include (but are not limited to) responsibilities of the job, education, experience, knowledge, skills, and abilities, as well as internal equity, alignment with market data, applicable bargaining agreement (if any), or other law.