Full-timeTech & engineering· Posted 13 Aug

Principal Data Scientist (User Understanding Platformisation)

GrabApply on company site

Salary

Not stated by the company

When

Full-time hours

Where

SingaporeGrab One North Singapore office

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Start: Not stated
Work mode: On-site
Experience: Experienced

About the role

You will be part of the Search and Personalization team, working alongside engineers and data scientists to build machine learning capabilities that help users discover food, groceries, mobility and services across Southeast Asia. Based onsite at the Grab One North Singapore office, this is a senior individual contributor role reporting to the Head of Data Science, Business Ecosystem, focused on user understanding platformisation and generative recommendation. It suits an experienced data scientist who can set technical direction and work across Data Science, Engineering and Product.

What you'll do

Define the technical strategy and roadmap for user understanding and generative personalization, identifying shared ML capabilities across search, recommendation, chatbot and other personalized experiences.

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Architect and develop large-scale user understanding systems that capture long-term preferences, real-time intent, behavioural patterns, interests and contextual signals from diverse user interactions.

Develop reusable user representations and foundation models supporting downstream tasks such as retrieval, ranking, recommendation, conversational personalization, targeting and engagement.

Advance generative recommendation by exploring foundation models, generative retrieval, sequence modeling and unified user-item representations.

Drive platformization of user understanding, turning modelling approaches into reusable representations, models, features, APIs and serving systems adopted by multiple teams.

Establish offline and online evaluation methodologies to measure quality, generalizability and incremental impact of user understanding and generative models.

Partner with senior machine learning and platform engineers to design production architectures for large-scale model training, representation generation, real-time user understanding and low-latency serving.

Evaluate emerging research in generative recommendation, foundation models, user modeling, generative retrieval and representation learning, and lead promising approaches from research and prototypes into production.

Good to know

Based onsite in the Grab One North Singapore office.
FlexWork arrangements such as differentiated hours are available.

Requirements

Master's Degree in Computer Science, Machine Learning, Artificial Intelligence, Operations Research, or another quantitative field, or equivalent practical experience developing large-scale machine learning systems
At least 7 years of relevant industry experience, including substantial experience designing and deploying production deep learning systems for recommendation, search, user modelling, NLP, or related applications at scale
Expertise and technical leadership in user modelling, recommendation systems, information retrieval, representation learning, or sequence modelling, with experience transforming large-scale behavioural data into representations that generalise across multiple downstream tasks
Expertise with modern deep learning architectures, including Transformers and sequence-based models, with hands-on proficiency in frameworks such as PyTorch, TensorFlow
Experience designing large-scale ML systems, including distributed training, feature and embedding computation, real-time user representations, online inference, latency optimization, model monitoring, and retraining
Proficiency in Python and experience with large-scale data processing technologies such as Spark, Scala, or equivalent distributed data systems

Benefits

Term Life Insurance and comprehensive Medical Insurance
GrabFlex benefits package
Parental and Birthday leave
Love-all-Serve-all (LASA) volunteering leave
Confidential Grabber Assistance Programme
FlexWork arrangements such as differentiated hours

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Principal Data Scientist (User Understanding Platformisation)

About the role

What you'll do

Good to know

Requirements

Benefits

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