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Remote Neo4J Jobs in Washington (NOW HIRING)

Bachelor's degree in Geospatial Intelligence, Geography, Remote Sensing, Intelligence Studies ... Neo4j, or JanusGraph. * Experience developing graph traversal capabilities using Apache TinkerPop ...

Data Engineer

Chantilly, VA · On-site +1

$117K - $140K/yr

... neo4J, MariaDB, Postgres, Docker, Puppet, and many others. Work on this program takes place in McLean, VA and in various field offices throughout Northern VA (we cannot support remote work) and ...

Data & Software Engineer

Mclean, VA · Remote

$115K - $139K/yr

... neo4J, MariaDB, Postgres, Docker, Puppet, and many others. Work on this program takes place in McLean, VA and in various field offices throughout Northern VA (we cannot support remote work) and ...

Data & Software Engineer

Mclean, VA · On-site +1

$150K - $250K/yr

... neo4J, MariaDB, Postgres, Docker, Puppet, and many others. Work on this program takes place in McLean, VA and in various field offices throughout Northern VA (we cannot support remote work) and ...

Data Engineer

Chantilly, VA · On-site +1

$150K - $200K/yr

... neo4J, MariaDB, Postgres, Docker, Puppet, and many others. Work on this program takes place in McLean, VA and in various field offices throughout Northern VA (we cannot support remote work) and ...

Remote Neo4J information

What are the most commonly searched types of Neo4J jobs in Washington? The most popular types of Neo4J jobs in Washington are:
Infographic showing various Remote Neo4J job openings in Washington as of July 2026, with employment types broken down into 71% Full Time, 7% Part Time, and 22% Contract. Highlights an 11% In-person, and 89% Remote job distribution.

Graph Data Scientist

Magnus Management Group LLC

Washington, DC • Remote

Full-time

Medical, Dental, Vision, Retirement, PTO

Posted 27 days ago


Job description

Benefits:
  • 401(k)
  • Dental insurance
  • Health insurance
  • Paid time off
  • Vision insurance

We are seeking a Graph Data Scientist to develop advanced graph analytics supporting fraud investigations across complex federal programs. The successful candidate will leverage Neo4j, graph algorithms, and machine learning to identify hidden relationships, organized fraud rings, and emerging fraud patterns.
Responsibilities:
  • Shall have three (3) or more years of hands-on experience using Neo4j or a similar graph database and fluency in Cypher, or similar query language, to detect potential fraud using leading edge techniques and best practices. 
  • Must have a deep understanding of network typology, centrality measures, community detection, and shortest path algorithms; using a multitude of public and nonpublic data sources. 
  • Must have three (3) or more years of hands-on experience in statistical and machine learning foundations, clustering, classifiers and anomaly detection as applied to graph structured data. 
  • Must have three (3) or more years of hands-on experience applying graph methods to fraud detection and knowledge graphs. 
  • Should have experience designing, implementing, and optimizing graph data pipelines, data models, and schemas that support large‑scale, high‑complexity networks, preferably within large federal benefit programs. 
  • Should have strong Python skills using standard machine learning libraries are required. 
Minimum Qualifications
  • Minimum 3 years using Neo4j or similar graph database. 
  • Minimum 3 years developing graph analytics for fraud detection. 
  • Experience with Cypher query language. 
  • Strong Python programming skills. 
  • Experience with graph algorithms including: 
    • Community Detection 
    • Centrality Measures 
    • Shortest Path 
    • Link Analysis 
    • Network Topology 
  • Experience with machine learning applied to graph data. 

This is a remote position.