Senior Data Scientist (Fulfillment)

Data Science; Singapore; On-site; SGD 80,000 - 120,000; Full time

Job summary

A leading tech firm is seeking a Senior Data Scientist to optimize fulfilment strategies at their Singapore office. You will enhance operational efficiency through advanced machine learning models and lead the development of systems that can adapt to dynamic marketplace conditions. Responsibilities include designing strategies, collaborating with engineers, and presenting solutions. Ideal candidates should have a strong background in machine learning, predictive modelling, and the ability to communicate technical insights effectively.

Qualifications

• Experience leading data-driven optimization and automation projects.
• Strong background in machine learning and data science methodologies.
• Ability to translate complex technical findings to non-technical stakeholders.

Responsibilities

• Design cross-system fulfilment strategies to enhance operational efficiency.
• Develop advanced models to capture spatial-temporal patterns.
• Integrate ML/DL models into real-time production systems.
• Create technical documents and present solutions effectively.

Skills

Deep Learning (DL)

Reinforcement Learning (RL)

Predictive Modelling

Data Analysis

Operational Efficiency Optimization

Job description

Get to Know the Team

The Fulfilment Tech Family is a foundational part of Grab, enabling seamless coordination between our diverse marketplaces across Southeast Asia. We design real-time, distributed systems and machine learning solutions to process hundreds of millions of requests per day, driving efficient supply allocation, pricing, and order matching. Our mission:

• Deliver best-in-class products for our driver-partners.
• Maximise efficiency in fulfilling consumer demand – rain or shine.
• Create sustainable, efficient marketplaces that balance experience and cost for all stakeholders.

We're looking for a Senior Data Scientist to join our Fulfilment team and take the lead in Fulfilment strategy optimization – bringing existing optimisation and automation of our pricing, dispatch and supply management policies to the next level.

Get to Know the Role

You’ll optimize cross-system fulfilment strategies, and lead model development with user and driver behavioural prediction, optimisation and reinforcement learning (RL) techniques. Your primary objective will be to enhance marketplace operations by constructing interpretable, adaptable multi-agent RL systems or decision agents that can manage diverse objectives and disruptions.

You’ll report to the Head of Data Science and work onsite at Grab’s One North Singapore office.

The Critical Tasks You Will Perform

• You’ll design and implement cross-system strategies to improve operational efficiency in fulfilling user demands and boosting driving utilisation.
• You’ll build advanced DL and LLM models to capture the spatial-temporal patterns of dynamic marketplace conditions.
• You’ll develop advanced ML/DL models to predict user and driver behaviours, and use the behavioural insights to inform decision‑making and platform interventions.
• You’ll build and deploy interpretable, adaptable optimisation models, RL systems or decision agents that can handle multi‑objectives and real‑world disruptions.
• You’ll collaborate with machine learning engineers and backend engineers to integrate the ML/DL, optimisation or RL models into real‑time production systems.
• You’ll create technical documents outlining the methodologies and findings of your work. You’ll also present solutions to non‑technical stakeholders.