Senior Data Scientist

The Senior Data Scientist will support the NDOC DOMEX Technology Platform, focusing on building data intelligence pipelines, graph and Elasticsearch based analytics, and collaboration to advance a future-state DOMEX Data Discovery Platform for national security.

Location

Bethesda, MD (onsite)

Compensation

Salary range: USD 107,900 - 195,050 per year

Requirements

• Education: Master’s degree in Computer Science, Data Science, or a related field; experience: 6–10 years with a Master’s degree, or 8–12 years with a Bachelor’s degree.
• Active Top Secret/SCI clearance with the ability to obtain and maintain a Polygraph.
• Proficiency in Elasticsearch/OpenSearch architecture, index design, mappings, analyzers, and query optimization.
• Experience with graph databases such as JanusGraph, Neo4j, TigerGraph, Amazon Neptune, or Memgraph.
• Knowledge of graph analytics frameworks and algorithms, including traversal, centrality, community detection, similarity analysis, and link prediction.
• Experience training Neural Networks, including data selection for training, evaluation, and testing.
• Experience constructing static and interactive visualizations and dashboards, including link charts.
• Proficiency in Python.

Responsibilities

• Analyze large data sets across diverse structures to identify patterns and develop dashboards that initiate discovery and present results.
• Utilize Elasticsearch/OpenSearch and graph-based platforms to uncover and analyze complex data relationships.
• Explore embedding space solutions to enhance search and discovery over structured datasets such as source code repositories and document references.
• Investigate graph-structure analysis to reveal intricate network meta-paths and meta-structures across heterogeneous graphs.
• Design statistical approaches to manage near-duplicate data and uncertain relationships.
• Respond to Government Data Science requests to discover and report insights within graph representations, including custom dashboards, query optimization, and transforming datasets into canonical graph structures.
• Design and optimize Elasticsearch indices to efficiently support large-scale hierarchical classification structures with high-performance search, aggregation, and updates.
• Assist data engineering in designing, implementing, and maintaining a graph data store optimized for large, dense batch updates and high-throughput analytics.
• Prototype ingestion pipelines that enable scalable graph analytics.
• Contribute to 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 Kubernetes 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.
• Work 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, policy compliance, 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 and applications.
• Provide input to software components of system design, including hardware/software trade-offs, software reuse, use of COTS/GOTS, and requirements analysis from system level to individual components.

Technologies

• Elasticsearch
• OpenSearch
• JanusGraph
• Neo4j
• TigerGraph
• Amazon Neptune
• Memgraph
• Kubernetes
• Python
• Linux
• CI/CD pipelines
• Graph Neural Networks (GCN, GTNs)

Benefits

• Health and Wellness programs
• Income Protection
• Paid Leave
• Retirement