Job Description

Get to Know the Team

The GrabX team, a part of Grab's Tech Infra, builds and maintains the experimentation platform used across all Grab's marketplaces. We help product and engineering teams make data-driven decisions by providing tools for A/B testing, statistical analysis, and measurement of business-critical metrics.

Our mission:

• Enable reliable, scientifically sound experimentation for all product teams
• Develop causal inference and statistical methodologies to measure impact accurately
• Ensure the integrity, scalability, and performance of the core experimentation platform

We are looking for a Senior Data Scientist to join the GrabX team and lead the data science strategy for our experimentation platform—bringing statistical rigor and innovative methodologies to drive platform evolution and reliable decision-making across Grab.

Get to Know the Role

You'll shape the future of experimentation at Grab. You'll optimize and develop A/B testing methodologies, ensure metric reliability, and grow the platform's capabilities for complex experimental designs. This includes developing solutions for platform contamination, sample ratio mismatch, and network effects, all within our distributed infrastructure environment.

You'll report to the GrabX Engineering Manager and work onsite at Grab's One North Singapore office.

The Critical Tasks You will Perform

• You will design, implement, and validate statistical and causal inference methodologies to improve the accuracy and efficiency of A/B tests (e.g., variance reduction, sequential testing, quasi-experimental methods).
• You will partner with platform engineers to translate statistical concepts into production-ready features within the GrabX experimentation platform.
• You will define and standardise key business and product metrics, establishing monitoring and validation pipelines to ensure data quality and metric reliability for all experiments.
• You will provide guidance to product teams on experimental design, power analysis, and result interpretation—conducting complex experiments and communicating findings to both technical and non-technical stakeholders.
• You will develop and implement solutions for automated experiment analysis, using AI agents or MCPs to grow data-driven insights.

Job Requirements