Senior Data Scientist (Trust & Fraud)
Core
Architect scalable data science solutions to shield the Grab ecosystem from fraud and safety threats by deploying sequence-based models and graph algorithms.
Role type
Senior Individual Contributor Data Scientist (Trust & Fraud)
Builds
Fraud detection systems integrating traditional ML and agentic LLM systems for payment risk and money laundering networks
Domain
Fintech / Platform Security / Deep Learning
Deliverable
production ML models
Required skills
Python, SQL, Spark, TensorFlow, PyTorch, XGBoost, LightGBM, Scikit-learn, Graph Neural Networks (GNNs), Transformers, RNNs, CNNs, LLM foundations (RAG), LangGraph, LangChain
Preferred skills
Generative AI tools usage, synthetic data generation, agentic system design
Technologies
Qwen, LangGraph, LangChain, Claude subagents, Spark
Responsibilities
Architect scalable data science solutions translating operational challenges into strategic wins; Conduct cutting-edge research to incorporate latest algorithms and generative AI into defense systems; Master data orchestration by preparing, augmenting, and combining diverse data types including LLM-generated synthetic data; Design, train, and fine-tune model architectures using GNNs, Transformers, and Gradient Boosted Trees; Lead end-to-end model lifecycle from production deployment to performance monitoring; Leverage Generative AI tools to accelerate code generation and automate testing.
Seniority
Senior, hands-on IC
