Neo4j Graph Data Engineer for Fraud Analytics

Neo4j Graph Data Engineer for Fraud Analytics

Full-Time 60000 - 80000 Β£ / year (est.) No working from home possible
ELLIOTT MOSS CONSULTING PTE. LTD.

At a Glance

  • Tasks: Design graph-based analytics for fraud detection and AML investigations using Neo4j.
  • Company: Join ELLIOTT MOSS CONSULTING, a leader in innovative data solutions.
  • Benefits: Competitive salary, health benefits, and opportunities for professional growth.
  • Other info: Collaborative environment with a focus on cutting-edge technology.
  • Why this job: Make a real impact by tackling fraud and enhancing banking security.
  • Qualifications: Experience with Neo4j and strong analytical skills required.

The predicted salary is between 60000 - 80000 Β£ per year.

ELLIOTT MOSS CONSULTING PTE. LTD. seeks a Senior Neo4j Graph Data Engineer to design graph-based analytics for fraud detection and AML investigations. You will model complex banking relationships in Neo4j, apply Graph Data Science, develop investigation dashboards and collaborate with Risk, AML, Compliance and Data Science teams to identify suspicious activities and interconnected fraud networks.

Neo4j Graph Data Engineer for Fraud Analytics employer: ELLIOTT MOSS CONSULTING PTE. LTD.

ELLIOTT MOSS CONSULTING PTE. LTD. is an exceptional employer that fosters a collaborative and innovative work culture, perfect for those passionate about AI and technology. Located in a vibrant tech hub, employees benefit from continuous growth opportunities, access to cutting-edge resources, and a supportive environment that encourages creativity and professional development. Join us to be part of a forward-thinking team dedicated to solving real-world challenges with advanced AI solutions.

ELLIOTT MOSS CONSULTING PTE. LTD.

Contact Details:

ELLIOTT MOSS CONSULTING PTE. LTD. Recruitment Team

We think you need these skills to ace Neo4j Graph Data Engineer for Fraud Analytics

Communication Skills
Problem-Solving Skills
SQL
Python
Data Engineering
Automation
Data Pipeline Development