Graph Data Scientist

Role Summary

We are looking for a highly skilled Graph Data Scientist to design and develop graph-based analytical solutions leveraging Neo4j/TigerGraph and advanced data science techniques. The role will focus on building knowledge graphs, detecting complex patterns, and enabling AI-driven insights.

Key Responsibilities

Design and develop graph data models using Neo4j/TigerGraph

Build and manage knowledge graphs for enterprise use cases (fraud detection, relationship mapping, pattern discovery)

Apply data science and ML techniques to extract insights from graph data

Develop graph algorithms (pathfinding, centrality, clustering, anomaly detection)

Integrate graph platforms with Gen AI/LLM-based systems for intelligent decision-making

Collaborate with engineering and AI teams to embed graph insights into applications

Required Skills

Strong experience in Neo4j, TigerGraph, or similar graph databases

Solid background in data science (Python, Pandas, Scikit-learn, PyTorch/TensorFlow)

Experience in graph algorithms and network analysis

Hands-on with data modeling, ETL, and large-scale data processing

Understanding of Gen AI / LLM integration with structured data systems

Preferred

Experience with knowledge graphs and semantic data models

Exposure to hybrid architectures combining graph + AI systems