Senior Principal Data Scientist (Fulfilment)

{"@context":"https://schema.org","@type":"JobPosting","title":"Senior Principal Data Scientist (Fulfilment)","description":"\u003Cp\u003E\u003Cstrong\u003EAbout Grab and Our Workplace\u003C/strong\u003E\u003C/p\u003E\u003Cp\u003EGrab is Southeast Asia\u0027s leading superapp. From getting your favourite meals delivered to helping you manage your finances and getting around town hassle-free, we\u0027ve 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.\u003C/p\u003E\u003Cp\u003E\u003Cstrong\u003EGet to Know the Team\u003C/strong\u003E\u003C/p\u003E\u003Cp\u003EThe Fulfilment Tech Family builds the systems that power Grab\u0027s marketplaces across Southeast Asia. We design real-time, distributed systems and Machine Learning (ML) solutions that process hundreds of millions of requests each day. Our work drives supply allocation, pricing, and order matching for millions of users and driver-partners.Our mission is three-fold:\u003C/p\u003E\u003Cul\u003E\u003Cli\u003EDeliver products that work for our driver-partners\u003C/li\u003E\u003Cli\u003EMeet consumer demand, regardless of conditions\u003C/li\u003E\u003Cli\u003EBuild marketplaces that balance experience and cost for everyone involved\u003C/li\u003E\u003C/ul\u003E\u003Cp\u003EWe are looking for a Senior Principal Data Scientist to lead our shift toward automated marketplace optimization. You\u0027ll advance how we use data and ML to automate pricing, dispatch, and supply management decisions.\u003C/p\u003E\u003Cp\u003E\u003Cstrong\u003EGet to Know the Role\u003C/strong\u003E\u003C/p\u003E\u003Cp\u003EThis is a Senior Principal individual contributor role where you\u0027ll build the foundation for autonomous, learning-driven marketplace systems. You\u0027ll work at the intersection of reinforcement learning, large language models, and production systems that operate at scale.\u003C/p\u003E\u003Cp\u003EYour work centres on two areas:\u003C/p\u003E\u003Cul\u003E\u003Cli\u003E\u003Cstrong\u003EReinforcement Learning (RL) Systems:\u003C/strong\u003E You\u0027ll develop systems that jointly optimize pricing, dispatching, and supply repositioning. You\u0027ll build decision agents that handle multiple objectives and adapt when real-world conditions change.\u003C/li\u003E\u003Cli\u003E\u003Cstrong\u003ELLM-Based Behavioural Intelligence:\u003C/strong\u003E You\u0027ll architect systems using fine-tuned language models to predict, explain, and simulate user decision-making at scale. These models will power the next generation of marketplace automation.\u003C/li\u003E\u003C/ul\u003E\u003Cp\u003EYou\u0027ll serve as the technical lead for a small team, guiding both research direction and production implementation. You\u0027ll report to the Head of Data Science and work from Grab\u0027s One-North Singapore office.\u003C/p\u003E\u003Cp\u003E\u003Cstrong\u003EThe Critical Tasks You will Perform\u003C/strong\u003E\u003C/p\u003E\u003Cp\u003EYou\u0027ll:\u003C/p\u003E\u003Cul\u003E\u003Cli\u003EDesign and implement end-to-end RL systems that combine model-based RL, offline RL, simulation, and online learning into a unified training pipeline. This includes creating state representations and reward structures that balance short-term results with long-term outcomes.\u003C/li\u003E\u003Cli\u003EBuild latent world models and marketplace state representations that capture supply-demand interactions, location-based patterns, and behavioural signals from users and drivers.\u003C/li\u003E\u003Cli\u003EDevelop systems that optimize across multiple marketplace levers simultaneously\u2014pricing, dispatching, and supply repositioning\u2014to expand the set of achievable outcomes for the business.\u003C/li\u003E\u003Cli\u003ECreate policy evaluation frameworks and establish monitoring systems that allow safe deployment of new decision-making policies in production.\u003C/li\u003E\u003Cli\u003EFine-tune open-source large language models on domain-specific data to build capabilities for prediction, reasoning, and simulation within marketplace applications.\u003C/li\u003E\u003Cli\u003EDesign and implement training strategies for language models, including supervised fine-tuning, preference-based alignment, and iterative improvement methods.\u003C/li\u003E\u003Cli\u003EWork with data engineers and backend engineers to integrate RL and LLM systems into real-time production environments serving millions of users.\u003C/li\u003E\u003C/ul\u003E\u003Cp\u003E\u003Cstrong\u003EWhat Essential Skills You Will Need\u003C/strong\u003E\u003C/p\u003E\u003Cul\u003E\u003Cli\u003E\u003Cstrong\u003EYou have PhD in Computer Science, Operations Research, Applied Mathematics, or related field with at least 10 years of experience\u003C/strong\u003E \u2014 to lead complex technical initiatives spanning research and production systems.\u003C/li\u003E\u003Cli\u003E\u003Cstrong\u003EYou are proficient in RL fundamentals\u003C/strong\u003E \u2014 including Markov Decision Processes, stochastic control, and reward design trade-offs. You\u0027ll apply these to build closed-loop systems that make sequential decisions in the marketplace.\u003C/li\u003E\u003Cli\u003E\u003Cstrong\u003EYou have experience building production ML/ RL systems with online learning or simulation-based optimization\u003C/strong\u003E \u2014 to deploy models that learn and adapt in real-time environments.\u003C/li\u003E\u003Cli\u003E\u003Cstrong\u003EYou have knowledge in world models and sequential modelling\u003C/strong\u003E \u2014 including latent dynamic models (RNNs, transformers, state-space models) and representation learning for complex systems. You\u0027ll use these to model marketplace dynamics accurately.\u003C/li\u003E\u003Cli\u003E\u003Cstrong\u003EYou have hands-on experience fine-tuning large language models in production\u003C/strong\u003E \u2014 including supervised fine-tuning and at least one preference-based alignment method (RLHF, DPO, or GRPO). You\u0027ll apply parameter-efficient methods (LoRA, QLoRA, or PEFT) and understand their trade-offs in accuracy, memory, and cost.\u003C/li\u003E\u003Cli\u003E\u003Cstrong\u003EYou can design evaluation frameworks for generative models\u003C/strong\u003E \u2014 including metrics for factual accuracy and reasoning quality. You\u0027ll use these to validate model outputs before deployment.\u003C/li\u003E\u003Cli\u003E\u003Cstrong\u003EYou have experience with distributed training frameworks\u003C/strong\u003E \u2014 such as DeepSpeed, FSDP, or Megatron-LM. You\u0027ll use these to train large models efficiently across multiple GPUs or nodes.\u003C/li\u003E\u003Cli\u003E\u003Cstrong\u003EYou are proficient in Python and ML frameworks (PyTorch or TensorFlow)\u003C/strong\u003E \u2014 to implement models and integrate with production codebases.\u003C/li\u003E\u003Cli\u003E\u003Cstrong\u003EYou have experience with scalable computing platforms\u003C/strong\u003E \u2014 such as Spark or Ray. You\u0027ll use these to process large datasets and distribute training workloads.\u003C/li\u003E\u003Cli\u003E\u003Cstrong\u003EYou can translate ambiguous business problems into concrete modelling tasks\u003C/strong\u003E \u2014 to identify what can be solved with ML/RL and define the scope, data requirements, and success criteria.\u003C/li\u003E\u003C/ul\u003E\u003Cp\u003E\u003Cstrong\u003ELife at Grab\u003C/strong\u003E\u003C/p\u003E\u003Cp\u003EWe care about your well-being at Grab, here are some of the global benefits we offer:\u003C/p\u003E\u003Cul\u003E\u003Cli\u003EWe have your back with \u003Cstrong\u003ETerm Life Insurance \u003C/strong\u003Eand comprehensive \u003Cstrong\u003EMedical Insurance.\u003C/strong\u003E\u003C/li\u003E\u003Cli\u003EWith \u003Cstrong\u003EGrabFlex, \u003C/strong\u003Ecreate a benefits package that suits your needs and aspirations.\u003C/li\u003E\u003Cli\u003ECelebrate moments that matter in life with loved ones through \u003Cstrong\u003EParental\u003C/strong\u003E and \u003Cstrong\u003EBirthday leave\u003C/strong\u003E, and give back to your communities through \u003Cstrong\u003ELove-all-Serve-all (LASA)\u003C/strong\u003E volunteering leave\u003C/li\u003E\u003Cli\u003EWe have a confidential \u003Cstrong\u003EGrabber Assistance Programme\u003C/strong\u003E to guide and uplift you and your loved ones through life\u0027s challenges.\u003C/li\u003E\u003Cli\u003EBalancing personal commitments and life\u0027s demands are made easier with our FlexWork arrangements such as differentiated hours\u003C/li\u003E\u003C/ul\u003E\u003Cp\u003E\u003Cstrong\u003EWhat We Stand For At Grab\u003C/strong\u003E\u003C/p\u003E\u003Cp\u003EWe are committed to building an inclusive and equitable workplace that provides equal opportunity for Grabbers to grow and perform at their best. We consider all candidates fairly and equally regardless of nationality, ethnicity, race, religion, age, gender, family commitments, physical and mental impairments or disabilities, and other attributes that make them unique.\u003C/p\u003E","identifier":"REF5249O","mainEntityOfPage":"https://www.grab.careers/en/jobs/744000123867849/senior-principal-data-scientist-fulfilment/","url":"https://www.grab.careers/en/jobs/744000123867849/senior-principal-data-scientist-fulfilment/","datePosted":"2026-04-30","employmentType":"FULL_TIME","hiringOrganization":{"@type":"Organization","name":"Grab","url":"https://www.grab.com/sg/","logo":"https://www.grab.careers/images/logo.svg"},"industry":"Data Science","jobLocation":{"@type":"Place","name":"Singapore","address":{"@type":"PostalAddress","name":"Singapore","addressCountry":"Singapore","addressLocality":"Singapore","streetAddress":"Grab One North"}}}