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