Fraud Analytics Graph Engineer (Neo4j)

Net2Source (N2S); Charlotte (NC); On-site; USD 90,000 - 120,000; Full time

Job summary

Net2Source (N2S) is searching for a Graph Database Engineer in Charlotte, NC, to design and deliver graph-based fraud detection solutions using Neo4j. The role includes modeling complex relationships to uncover fraud patterns, optimizing Cypher queries, and maintaining data pipelines. Candidates should have 4 to 8 years of IT experience with strong proficiency in graph databases and analytical skills. This contract position emphasizes collaboration with fraud analysts and data scientists.

Qualifications

• 4 to 8 years of overall IT experience.
• Strong hands-on experience with Neo4j Graph Database.
• Solid expertise in Cypher query language.
• Good understanding of graph data modeling and graph concepts.
• Experience with fraud, AML, risk, or financial analytics use cases.

Responsibilities

• Design and implement Neo4j graph data models for fraud and risk analytics.
• Develop, optimize, and maintain Cypher queries for deep relationship traversal.
• Support fraud use cases such as entity resolution and fraud rings.
• Build and maintain data ingestion pipelines from various sources.
• Perform query tuning, indexing, and schema optimization.
• Integrate Neo4j with applications and services.
• Collaborate with other teams to translate requirements into graph solutions.
• Assist in production support, troubleshooting, and monitoring graph platforms.

Skills

Neo4j Graph Database

Cypher query language

Python

Java

Analytical skills

Job description

Net2Source (N2S) is searching for a Graph Database Engineer in Charlotte, NC, to design and deliver graph-based fraud detection solutions using Neo4j. The role includes modeling complex relationships to uncover fraud patterns, optimizing Cypher queries, and maintaining data pipelines. Candidates should have 4 to 8 years of IT experience with strong proficiency in graph databases and analytical skills. This contract position emphasizes collaboration with fraud analysts and data scientists.