Senior Data Scientist (Trust & Fraud)

Get to Know Our Team

We are architects of trust. Our mission: shield Grab ecosystem from evolving fraud and safety threats by turning massive datasets into applicable intelligence. From deploying sequence-based models for payment risk to applying graph algorithms that unmask complex money laundering networks, we operate at intersection of deep learning and platform security. We innovate constantly, researching latest methods to neutralise tactics before they surface.

Get to Know the Role

You fight fraud by analysing transactional data, developing and deploying machine learning models, and collaborating with cross-functional teams to integrate fraud detection systems. Reporting to Executive Director, Data Science and Analytics, you will work as Individual Contributor in full-time on-site role at Grab KL office. You will push boundaries of machine learning and LLM applications at super-app scale, growing expertise in cutting-edge agentic systems. Apply today to help keep Grab platform safe and trustworthy!

The Critical Tasks You Will Perform

• You will partner with teams to architect scalable data science solutions that translate complex operational challenges into strategic wins, integrating traditional ML and agentic LLM systems.
• You will conduct research to incorporate advancements in algorithms and generative AI into defense systems to counter emerging fraud tactics.
• You will master data orchestration by preparing, augmenting, and combining diverse data types to build high-fidelity training datasets, using LLMs to generate synthetic data and labels.
• You will design, train, and fine-tune model architectures, utilizing Graph Neural Networks (GNNs), Transformers, fine-tuned open-source LLMs (like Qwen), and Gradient Boosted Trees.
• You will lead end-to-end lifecycle of models—from production deployment to performance monitoring—iterating alongside software and product engineering teams.
• You will leverage Generative AI tools (like coding assistants and analytical co-pilots) in daily workflows to accelerate code generation, automate testing, and enhance overall productivity.

Function: Engineering
Experience Level: Associate