Software Developer - Neo4J

Key Responsibilities Design and implement graph data models using Neo4j for customers, accounts, transactions, devices, and related entities. Develop and optimize Cypher queries for graph analytics and data retrieval. Build ETL pipelines and data processing workflows using Python. Apply Graph Data Science algorithms such as Community Detection, Link Prediction, Node Embeddings, Pathfinding, and Centrality analysis. Develop graph visualization dashboards using Neo4j Bloom or similar visualization tools. Optimize graph database performance through indexing, query tuning, and data model improvements. Collaborate with Risk, Compliance, AML, Data Science, and business teams to understand requirements and deliver technical solutions. Support production environments by monitoring, troubleshooting, and improving graph database performance. Stay updated with emerging graph technologies and contribute to continuous improvements. Requirements Minimum Qualifications Bachelor's or Master's degree in Computer Science, Information Technology, Data Science, or a related discipline. 5–6 years of overall IT experience. At least 2 years of hands-on experience with Neo4j and Cypher Query Language. Experience with Neo4j Graph Data Science (GDS) library. Strong Python programming skills for ETL, data processing, and graph analytics. Good understanding of graph database concepts including data modelling, indexing, query optimization, and performance tuning. Experience implementing Graph Data Science algorithms such as: Community Detection (Louvain, Label Propagation)Link Prediction Node Embeddings (Node2Vec, GraphSAGE)Centrality Measures Experience with Neo4j Bloom or similar graph visualization tools. Strong analytical, problem-solving, and communication skills. Ability to work collaboratively with cross-functional teams. Preferred Skills Experience in Banking, Fraud Detection, Anti-Money Laundering (AML), or Financial Crime domains. Experience with graph databases such as Amazon Neptune, TigerGraph, or JanusGraph. Knowledge of machine learning frameworks including scikit-learn, TensorFlow, or PyTorch. Experience with AWS, Azure, or Google Cloud Platform. Knowledge of Kafka or Kinesis for real-time data streaming. Familiarity with CI/CD pipelines, Infrastructure as Code (Terraform or CloudFormation), and DevOps practices. Understanding of AML, KYC, and financial crime compliance frameworks. Neo4j Certified Professional or Graph Data Science certification is an advantage. EA Number : 11C4879