About Grab and Our Workplace

Grab is Southeast Asia's leading superapp. From getting your favourite meals delivered to helping you manage your finances and getting around town hassle-free, we've got your back with everything. In Grab, purpose gives us joy and habits build excellence, while harnessing the power of Technology and AI to deliver the mission of driving Southeast Asia forward by economically empowering everyone, with heart, hunger, honour, and humility.

Get to Know the Team

You'll join the Data Science team focused on grocery and retail services across our region. The team builds intelligent systems that make shopping more intuitive—from predicting what customers need before they search, to ensuring fresh groceries arrive on time. We work with Engineering, Product, and Operations teams to turn complex data challenges into practical solutions that serve millions of customers and merchant partners daily.

Get to Know the Role

You'll own data science projects from problem definition through to production deployment. Your work will directly shape how customers discover products, how we predict demand across neighbourhoods, and how we balance supply with real-time demand. You'll architect ML solutions, build predictive models, and deploy services that operate at scale. You'll also guide the team's technical direction and contribute to our research and IP portfolio.

The Critical Tasks You will Perform

You will:

• Architect and deploy agentic AI systems that predict shopping intent and power autonomous shopping assistants—allowing conversational discovery, automated reordering, and personalised recommendations for grocery and retail customers.
• Build spatio-temporal demand forecasting models that process complex signals (transactional, behavioral, and geospatial data) to generate granular SKU-level predictions across multiple time horizons—optimizing inventory positioning and reducing stock-outs and waste.
• Develop supply-demand balancing algorithms that use contextual signals to adjust platform visibility and nudge demand—allowing real-time optimization of merchant and driver supply allocation across neighbourhoods.
• Create predictive models for order lifecycle reliability that identify high-risk orders prone to cancellation, predict fulfillment failures due to inventory gaps, and flag transactions requiring proactive intervention—safeguarding the end-to-end delivery experience.
• Design customer targeting and segmentation models that decode unique shopping patterns to identify underserved customer segments—driving sustainable demand growth through intelligent automated targeting.
• Establish ML production standards by implementing versioning, automated testing, and performance monitoring for ML pipelines—ensuring model reliability and allowing iteration.
• Lead technical roadmap development by evaluating latest methodologies, contributing to research publications, and building intellectual property that advances our AI capabilities in commerce.

What Essential Skills You Will Need

Domain Knowledge

• At least 5 years of demonstrated experience building data science solutions in E-commerce, Quick-Commerce, or Marketplace environments—with specific exposure to supply chain, inventory management, or customer behaviour modelling

ML Architecture & Model Development

• Build production ML/DL models, including:
  • Recommender systems for product discovery and personalization
  • Time-series forecasting with geospatial features
  • Optimization algorithms for resource allocation
  • Classification and anomaly detection models for risk prediction

Programming & Big Data Processing

• Proficiency in Python or Scala for model development and data processing (needed for all tasks)
• Experience with distributed computing frameworks (Spark, Flink, or equivalent) for processing datasets at terabyte scale

LLM and Agentic AI Development

• Experience fine-tuning large language models and building LLM-based applications
• Hands-on experience with agentic development frameworks (LangChain, AutoGPT, CrewAI, or similar) for building multi-step autonomous workflows

MLOps & Production Systems

• Experience implementing CI/CD pipelines for ML models and deploying models to production environments
• Proficiency in model versioning, A/B testing frameworks, and real-time performance monitoring

Advanced Quantitative Foundation

• Master's degree in Machine Learning, Statistics, Computer Science, Operations Research, or related field—providing the theoretical foundation to architect complex spatio-temporal models and optimization algorithms

Life at Grab

We care about your well-being at Grab, here are some of the global benefits we offer:

• We have your back with Term Life Insurance and comprehensive Medical Insurance.
• With GrabFlex, create a benefits package that suits your needs and aspirations.
• Celebrate moments that matter in life with loved ones through Parental and Birthday leave, and give back to your communities through Love-all-Serve-all (LASA) volunteering leave
• We have a confidential Grabber Assistance Programme to guide and uplift you and your loved ones through life's challenges.
• Balancing personal commitments and life's demands are made easier with our FlexWork arrangements such as differentiated hours

What We Stand For at Grab

We are committed to building an inclusive and equitable workplace that enables diverse Grabbers to grow and perform at their best. As an equal opportunity employer, we consider all candidates fairly and equally regardless of nationality, ethnicity, religion, age, gender identity, sexual orientation, family commitments, physical and mental impairments or disabilities, and other attributes that make them unique.