Senior Data Scientist

Build, deploy, and manage end-to-end ML models and AI agents for Grab's Financial Services across Southeast Asia, focusing on predictive models for product cross-sell, personalized messaging, and channel optimization.

Develop and implement generative AI solutions using LLMs, including prompt engineering, agent orchestration, and fine-tuning techniques.

Collaborate with engineering, compliance, and operations teams to create scalable AI solutions and optimize performance using MLOps practices.

5+ years of data science or ML experience required in developing and productionizing ML models.

Expertise in Python, Spark, SQL (Presto/Hive) and core ML concepts like Bagging, Boosting, Online Learning, and Recommendation Engines.

Hands-on experience with Agentic frameworks (LangGraph, LangSmith, LangChain) and LLM orchestration and evaluation.

Experience with MLOps tools such as MLflow, Kubeflow, TFX, SageMaker, plus scalable cloud deployment knowledge.

Experienced individual contributor comfortable working independently on complex ML and AI problems within financial services domain.

Demonstrates strong engineering discipline including clean coding, modular design, version control, and balancing model performance with business trade-offs (latency, cost, scalability).

Familiarity or interest in real-time ML streaming technologies like Flink SQL/SDK and generative AI agent frameworks indicates an advanced, applied skillset.