Senior Data Scientist (Trust & Fraud)

Grab is Southeast Asia's leading superapp, providing various services including food delivery, financial management, and transportation.

As a Senior Data Scientist (Trust & Fraud), you will play a crucial role in shielding the Grab ecosystem from evolving fraud and safety threats by turning massive datasets into applicable intelligence.

You will analyze transactional data, develop and deploy machine learning models, and collaborate with cross-functional teams to integrate fraud detection systems.

Responsibilities:

• Partner with teams to architect scalable data science solutions that translate complex operational challenges into strategic wins, integrating traditional ML and agentic LLM systems.
• Conduct research to incorporate advancements in algorithms and generative AI into defense systems to counter emerging fraud tactics.
• 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.
• 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 end-to-end lifecycle of 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 daily workflows to accelerate code generation, automate testing, and enhance overall productivity.

Qualifications:

• Degree in Computer Science, Physics, Statistics, Mathematics, Engineering, Economics, or related quantitative field.
• At least 3 years of experience with proficiency in Python and SQL, alongside practical experience using distributed engines like Spark to wrangle large-scale datasets.
• Hands-on experience building and deploying machine learning models using standard libraries such as TensorFlow, PyTorch, XGBoost, LightGBM, or Scikit-learn.
• Practical experience with deep learning architectures (Transformers, RNNs, CNNs) and traditional ML (Boosted Trees), demonstrating ability to choose optimal architecture for specific problems.
• Experience with LLM and Agentic system foundations (e.g., RAG, Transformers) and hands-on experience building or using frameworks like LangGraph, LangChain, or Claude subagents.
• Experience engaging with AI tools and emerging technologies to enhance productivity, improve workflows, and contribute new ideas.

Benefits:

• Term Life Insurance and comprehensive Medical Insurance.
• GrabFlex, a benefits package that suits your needs and aspirations.
• Parental and Birthday leave, and Love-all-Serve-all (LASA) volunteering leave.
• Confidential Grabber Assistance Programme to guide and uplift you and your loved ones through life's challenges.