Description

Lead end-to-end development of AI-driven fraud detection systems, from use case discovery to deployment.

This role is on-site.

Responsibilities

• Lead fraud use case discovery and develop advanced detection models using Machine Learning and Graph Analytics.
• Identify predictive variables and build comprehensive fraud feature catalogues.
• Build, validate, and deploy pilot fraud detection models in production environments.
• Collaborate with engineering teams to design low-latency scoring architectures.
• Drive model explainability, governance, and compliance while supporting challenger model validation.

Required Skills

• 8+ years of experience in data science, analytics, or related technical roles.
• Strong expertise in Fraud Analytics and Machine Learning model development.
• Proficiency in Graph Analytics for complex relationship mapping and detection.
• Experience with AI-driven solutions for fraud detection and prevention.
• Proven track record in feature engineering and predictive variable identification.
• Ability to explain complex technical concepts to technical and non-technical audiences.
• Strong analytical and problem-solving skills with a focus on billing and transactional data.

Key Skills

Education

Any Graduate