Graph Data Scientist

Job Summary

To support fraud investigations across complex federal programs, the full-time Graph Data Scientist will develop advanced graph analytics leveraging Neo4j, graph algorithms, and machine learning to identify hidden relationships and emerging fraud patterns in a fully remote environment.

Key responsibilities

• Utilize Neo4j or similar graph databases and fluency in Cypher to detect potential fraud using advanced techniques
• Apply statistical and machine learning foundations to graph structured data for fraud detection and knowledge graphs
• Design, implement, and optimize graph data pipelines and models that support large-scale, complex networks

Required qualifications

• Minimum 3 years of experience using Neo4j or a similar graph database
• Minimum 3 years of experience developing graph analytics specifically for fraud detection
• Strong proficiency in Python programming and experience with standard machine learning libraries
• Knowledge of graph algorithms, including community detection, centrality measures, and shortest path
• Experience applying machine learning techniques to graph data