Get to know the Team:
In the ACE (Online Deliveries, Omnicommerce) Data Science team, you are at the core of Grab鈥檚 largest business pillars. We build and deploy AI/ML models to power seamless user experiences across the food ecosystem鈥攆rom instant deliveries to restaurant reservations. Our mission is to enhance user satisfaction and platform efficiency by solving unique challenges in geospatial demand, proactive reliability, and transformative AI-driven discovery.
Get to know the role:
As a Senior Data Scientist, you will lead the development of intelligent systems that shape how millions of users interact with Grab. You will move beyond basic forecasting to build proactive, "self-healing" reliability systems and leverage Generative AI to redefine the user experience. Your key responsibilities are:
Strategic Demand Shaping: Architect solutions that steer demand toward higher serviceability. This includes shaping demand spatially and temporally (e.g., shifting users from On-Demand to Scheduled Orders) to optimize network throughput.
Grab Content Enrichment: Transform "thin" or unstructured data into rich, machine-readable metadata. You will build systems that power new in-app discoveries and serve external AI demands (e.g., ChatGPT or Google鈥檚 AI search).
Demand Generation & Growth: Identify "hidden" customer patterns across food and dining to unlock new demand for ACE.
Reliability & Dispute Arbitration: Predict friction before it happens. You will develop models to identify order risks and cancellation probabilities, automating "who is at fault" logic and facilitating proactive interventions to maintain platform trust.
Transformative GAI Experience: Lead the integration of Generative AI (GAI) to fundamentally evolve the current user journey and interface.
Build, Iterate, and Deploy: Own the end-to-end lifecycle of ML models, translating tens of millions of passenger interactions into production-grade solutions through rigorous A/B testing and monitoring.
Cross-Function Collaboration: Partner with product managers, engineers, analytics, design and operations teams to scale solutions.
Innovation: Contribute to team鈥檚 innovation and IP creation.