Senior Data Scientist - Business & Transaction Platform

About the role

The Business & Transaction Platform (BTP) Data Science team builds scalable machine learning algorithms and intelligent platforms that power transaction efficiency and platform reliability across Grab. This Senior Data Scientist role helps build in-house machine learning platforms and deploy production-grade ML and LLM solutions to solve complex business problems at scale. Reporting to the Senior Data Science Manager, it is a full-time individual contributor position based onsite at the One North office in Singapore.

Key responsibilities

• Design, develop and benchmark efficient deep learning and machine learning algorithms for large-scale prediction, classification and forecasting.
• Build, fine-tune and deploy state-of-the-art LLMs and ML pipelines into production platforms with engineering teams.
• Analyse multi-modal datasets and build data processing pipelines using distributed computing frameworks.
• Run offline evaluations and online A/B experiments to validate model accuracy, latency and business performance.
• Contribute to technical IP, prototypes and team best practices, and partner with Product, Engineering and Operations on scalable ML features.
• Use GenAI tools and modern development workflows to speed up code delivery, pipeline testing and documentation.

Required profile

• Master's or PhD in Computer Science, Operations Research, Mathematics, Data Science or a related quantitative field.
• At least 2 years of hands-on experience building, deploying and monitoring ML or deep learning models in production.
• Ability to turn ambiguous business and transaction challenges into measurable ML formulations.
• Experience using AI tools to improve productivity and workflows.

Required skills

• Python and PyTorch programming.
• SQL and Spark for distributed data processing.
• Understanding of ETL and large-scale data platform pipelines.
• Hands-on experience with transformer models, NLP architectures and LLM frameworks.

What we offer

• Term life insurance and medical insurance.
• Parental and birthday leave, plus volunteering leave.
• A confidential assistance programme.
• FlexWork arrangements such as differentiated hours.