Senior Principal Data Scientist (Fulfilment) at Kudo

Singapore, , Singapore -

Full Time

Start Date

Immediate

Expiry Date

26 May, 26

Salary

0.0

Posted On

25 Feb, 26

Experience

10 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Reinforcement Learning, Machine Learning, Deep Learning, Operations Research, Stochastic Control, Behavioural Modelling, Online Learning Systems, Sequential Decision Frameworks, Python, PyTorch, TensorFlow, Spark, Ray, Optimization, Data Modeling, Marketplace Elasticity

Industry

Software Development

Description

Company Description 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. Job Description Get to Know the Team The Fulfilment Tech Family is an integral part of Grab, connecting our wide-ranging marketplaces across Southeast Asia. We develop real-time distributed systems and machine learning solutions to process hundreds of millions of requests daily, ensuring efficient allocation of supply, pricing, and seamless order matching. Our mission: Build reliable and impactful products for driver-partners. Optimize the ability to fulfil consumer needs in any conditions. Develop sustainable marketplaces, balancing user experience and operational costs across stakeholders. We're hiring a Senior Principal Data Scientist to join the Fulfilment team. You're an individual contributor whom will lead strategic optimization initiatives that elevate pricing, dispatch, and supply management strategies. You'll combine in-depth data-driven methodologies with a strategic mindset to drive automation and marketplace efficiency. Get to Know the Role As a Senior Principal Data Scientist, you'll shape and advance cross-system Fulfilment strategies, accounting for how passengers and driver-partners respond to platform interventions. You'll leverage machine learning and operations research methodologies to optimize marketplace-level operational outcomes. Through joint optimization across systems—pricing, dispatch, and supply positioning—you'll design interpretable, adaptable, and multi-objective-aware Reinforcement Learning decision agents. You'll model marketplace behaviour and develop policies to automate key aspects of platform operations, contributing lasting impact for customers, driver-partners, and Grab. 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 will: Develop ML and DL models to improve generalisation and operational efficiency Create unified Reinforcement Learning architectures that coordinate multiple elements, including pricing, dispatch, and supply positioning, while balancing diverse marketplace objectives. Design frameworks for joint optimization of marketplace systems through hierarchical or multi-agent RL approaches that push the operational Pareto frontier. Explore representations of data that consider supply-demand signals, behaviour elasticity, and factors like weather, traffic, and user intent. Build interpretable models to capture passenger and driver decision-making across diverse scenarios and operational conditions. Devise feedback loops to respond to passenger and driver behaviour, considering geographical differences and behavioural patterns over time. Collaborate with data engineers and backend teams to refine and integrate optimization models into real-time production systems. Work with the platform and experimentation teams to validate models in live environments and drive iterative improvements. Guide technical teams by leading efforts in data science while fostering collaboration and excellence. Qualifications What Essential Skills You Will Need You have a Master Degree in Computer Science, Operations Research, Applied Mathematics, or related field with at least 10 years of relevant experience. You have experience with Reinforcement Learning, MDPs, stochastic control, or behavioural modelling under uncertainty. You have experience deploying ML models in online learning systems, sequential decision frameworks, or simulation-based techniques for optimization tasks. You have fluency in Python and experience with ML libraries such as PyTorch or TensorFlow for developing robust learning algorithms. You are familiar with tools such as Spark or Ray to build scalable workflows for data-driven optimization and training. You can bridge business challenges into concrete modelling problems with actionable outputs. You have advanced skills to interpret platform data and understand marketplace elasticity, user behaviour, and external environmental influences, contributing to actionable insights for real-world applications. Additional Information 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.

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Responsibilities

The Senior Principal Data Scientist will lead strategic optimization initiatives focusing on pricing, dispatch, and supply management by developing ML/DL models and unified Reinforcement Learning architectures. Key tasks involve designing frameworks for joint optimization across marketplace systems and building interpretable models to capture user decision-making.