Job Requirements:

• 5–6 years of overall IT experience, with 2+ years of hands-on experience working with Neo4j,Cypher query language, and Graph Data Science (GDS) library.

• Strong proficiency in Python for ETL pipelines, data processing, and integration with Neo4j GDS workflows.

• Solid understanding of graph database concepts,including data modelling, indexing, query optimisation, and performance tuning.

• Experience applying GDS algorithms such as Community Detection (Louvain, Label Propagation), Link Prediction, Node Embeddings (Node2Vec, GraphSAGE), and Centrality measures.

Familiarity with Neo4j Bloom or similar graph visualisation tools for building investigative dashboards.

• Experience with other graph databases (e.g.,Amazon Neptune, TigerGraph, JanusGraph).

• Knowledge of machine learning frameworks (e.g.,scikit-learn, TensorFlow, PyTorch) and integrating ML models with graph analytics.

• Familiarity with cloud platforms (AWS, Azure, GCP) and deploying Neo4j in cloud environments.

• Understanding of data streaming technologies (Kafka,Kinesis) for real-time fraud detection pipelines.

• Experience with CI/CD pipelines, Infrastructure as Code(Terraform, CloudFormation), and DevOps practices.

• Neo4j Certified Professional or Graph Data Science certification is a plus.

Interested candidates may apply directly to [email protected] for immediate processing.