Senior Data Scientist (Fulfillment) at Kudo

Singapore, , Singapore -

Full Time

Start Date

Immediate

Expiry Date

10 Apr, 26

Salary

0.0

Posted On

10 Jan, 26

Experience

2 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Data Science, Machine Learning, Deep Learning, Reinforcement Learning, Python, Optimization, Behavioural Modelling, Stochastic Control, Distributed Computing, Markov Decision Processes, Simulation-Based Optimization, Technical Documentation, Collaboration, Real-Time Systems, Adaptable Models, Multi-Agent Systems

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 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, optimization 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. Qualifications What Essential Skills You Will Need You hold a Master degree in Computer Science, Operations Research, Applied Mathematics, or related field with at least 2 years of relevant experience. You have professional experience or academic publications in Reinforcement Learning, Stochastic Control, Behavioural Modelling, Optimisation Under Uncertainty. You have experience developing and deploying ML models that incorporate online learning, Markov Decision Processes, or simulation-based optimization. You are fluent in Python and ML frameworks (e.g., PyTorch, TensorFlow). You are familiar with distributed computing systems or scalable training platforms (e.g., Spark, Ray). You can explore new ideas and learn new skills to accomplish tasks. 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

You will optimize cross-system fulfilment strategies and lead model development using user and driver behavioural prediction techniques. Your primary objective is to enhance marketplace operations through the construction of interpretable, adaptable multi-agent reinforcement learning systems.