Fraud-Fighting Data Scientist | ML & LLM Innovation

Data Science; Selangor; On-site; MYR 90,000 - 140,000; Full time

Job summary

Data Science in Malaysia is seeking a talented Data Scientist to combat fraud at scale. You will analyse transactional data, build and deploy ML models, and work with cross-functional teams to integrate fraud detection systems on-site in Petaling Jaya.

You will push the boundaries of ML and LLM applications, collaborating with software and product engineers, and leveraging GNNs, Transformers, and open-source LLMs to accelerate development and improve security across the Grab ecosystem.

Qualifications

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

Responsibilities

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

Job description

Data Science in Malaysia is seeking a talented Data Scientist to combat fraud at scale. You will analyse transactional data, build and deploy ML models, and work with cross-functional teams to integrate fraud detection systems on-site in Petaling Jaya.

You will push the boundaries of ML and LLM applications, collaborating with software and product engineers, and leveraging GNNs, Transformers, and open-source LLMs to accelerate development and improve security across the Grab ecosystem.