Principal Data Scientist - User Understanding Platformisation

About the role

Grab is hiring a Principal Data Scientist for its Search and Personalization team, which builds the intelligence behind user discovery and engagement across food, groceries, mobility and services in Southeast Asia. Reporting to the Head of Data Science, Business Ecosystem, the role is based onsite in the Grab One North Singapore office and focuses on user understanding platformisation and generative recommendation. It is a senior individual contributor position providing technical leadership.

Key responsibilities

• Define the technical strategy and roadmap for user understanding and generative personalization, identifying shared ML capabilities for search, recommendation, chatbot and other personalized experiences.
• Architect and develop large-scale systems that capture long-term preferences, real-time intent, behavioral patterns, interests and contextual signals.
• Develop reusable user representations and foundation models supporting retrieval, ranking, recommendation, conversational personalization, targeting and engagement.
• Advance generative recommendation, exploring foundation models, generative retrieval, sequence modeling and unified user-item representations.
• Drive platformization of user understanding, turning successful approaches into reusable representations, models, features, APIs and serving systems adopted by multiple teams.
• Establish offline and online evaluation methods to measure quality, generalizability and incremental impact.
• Partner with senior ML and platform engineers on production architectures for large-scale training, representation generation, real-time understanding and low-latency serving.
• Evaluate emerging research and lead promising approaches from prototype to production.

Required profile

• Masters degree in Computer Science, Machine Learning, AI, Operations Research or another quantitative field, or equivalent practical experience with large-scale ML systems.
• At least 7 years of industry experience, including substantial experience designing and deploying production deep learning systems for recommendation, search, user modelling, NLP or related applications.
• Technical leadership in user modelling, recommendation, information retrieval, representation learning or sequence modelling.
• Ability to bridge research and production systems, especially in generative recommendation and foundation models, and to define technical direction in ambiguous problem spaces.

Required skills

• Modern deep learning architectures such as Transformers and sequence-based models; PyTorch and TensorFlow.
• Large-scale ML systems: distributed training, feature and embedding computation, real-time representations, online inference, latency optimization, model monitoring and retraining.
• Python and large-scale data processing tools such as Spark or Scala.
• Experimentation and evaluation: offline evaluation, A/B testing, metric design.

What we offer

• Term life insurance and comprehensive medical insurance.
• GrabFlex benefits package.
• Parental and birthday leave, plus LASA volunteering leave.
• Confidential assistance programme.
• FlexWork arrangements such as differentiated hours.