Description

You will design and develop graph-based analytical solutions using Neo4j or TigerGraph to build knowledge graphs and enable AI-driven insights.

This role is on-site.

Responsibilities

• Design and develop graph data models for enterprise use cases such as fraud detection and relationship mapping.
• Build and manage knowledge graphs to detect complex patterns and support pattern discovery.
• Apply data science and ML techniques, including pathfinding, centrality, clustering, and anomaly detection algorithms.
• Integrate graph platforms with Gen AI/LLM-based systems to support intelligent decision-making.
• Collaborate with engineering and AI teams to embed graph insights into production applications.

Required Skills

• Strong experience with Neo4j, TigerGraph, or similar graph databases.
• 10+ years of experience in data science and large-scale data processing.
• Proficiency in Python, Pandas, Scikit-learn, and PyTorch/TensorFlow.
• Solid background in graph algorithms and network analysis.
• Hands-on experience with data modeling and ETL processes.
• Understanding of Gen AI and LLM integration with structured data systems.

Preferred Skills

• Experience with knowledge graphs and semantic data models.
• Exposure to hybrid architectures combining graph databases with AI systems.

Key Skills

Education

Any Graduate