{"id":1253905,"url":"https://alion.io/job/grabtaxi-principal-data-scientist","title":"Principal Data Scientist","company":{"id":328610,"name":"Grab","domain":"grabtaxi.dev","url":"https://alion.io/company/grabtaxi","size_band":null,"is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":null,"truth_index":null},"role":"Data Science","role_family":"Data Science","seniority":"lead","employment_type":"full_time","work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Singapore"],"countries":["SG"],"hiring_countries":[],"hiring_countries_total":0,"salary":{"min":18000,"max":27000,"currency":"SGD","period":"month","gross":true,"usd_annual":253692},"salary_estimate":null,"experience_years_min":7,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"A/B Testing","optional":false},{"name":"Machine Learning","optional":false},{"name":"NLP","optional":false},{"name":"Python","optional":false},{"name":"PyTorch","optional":false},{"name":"Recommender Systems","optional":false},{"name":"Scala","optional":false},{"name":"Spark","optional":false},{"name":"TensorFlow","optional":false},{"name":"Transformers","optional":false}],"status":"live","first_seen_at":"2026-09-21T00:00:00Z","employer_posted_date":null,"last_verified_at":"2026-09-21T00:00:00Z","board_verified":false,"closed_at":null,"days_open":30,"trust":{"level":"not_scored","repost_count":null,"flags":[],"days_open":30},"description":"Get to Know the Team\nYou will join our Search and Personalization team — a group of engineers and data scientists building the intelligence that helps millions of users discover and engage with food, groceries, mobility, and services across Southeast Asia. We work with engineering, product, and business teams to develop foundational machine learning capabilities that allow Grab to better understand users and deliver relevant experiences across the platform.\nGet to Know the Role\nReporting to the Head of Data Science, Business Ecosystem, you'll be based onsite in the Grab One North Singapore office. This is a Principal Data Scientist and senior individual contributor role in the Search and Personalization team, focusing on user understanding platformization and generative recommendation.\nYou will provide technical leadership in building shared user understanding capabilities that power personalized experiences across Grab, including search, recommendation, chatbot, notification, and other user-facing applications. You will work across Data Science, Engineering, and Product to shape the long-term technical direction, turn latest artificial intelligence research into practical solutions, and drive adoption of these capabilities across teams.\nThe Critical Tasks You Will Perform\nYou will define the technical strategy and roadmap for user understanding and generative personalization, identifying foundational ML capabilities that can be shared across search, recommendation, chatbot, and other personalized experiences.\nYou will architect and develop large-scale user understanding systems that capture long-term preferences, real time intent, behavioral patterns, interests, and contextual signals from heterogeneous user interactions across Grab.\nYou will develop reusable user representations and foundation models that support diverse downstream tasks, including retrieval, ranking, recommendation, conversational personalization, targeting, and engagement.\nYou will advance generative recommendation, exploring foundation models, generative retrieval, sequence modeling, and unified user-item representations to complement and evolve conventional retrieval and ranking architectures.\nYou will drive the platformization of user understanding, turning successful modeling approaches into reusable representations, models, features, APIs, and serving systems adopted by multiple teams.\nYou will establish rigorous offline and online evaluation methodologies to measure the quality, generalizability, and incremental impact of user understanding and generative models across downstream applications.\nYou will partner with senior machine learning and platform engineers to design production architectures for large-scale model training, representation generation, real-time user understanding, and low-latency serving.\nYou will evaluate emerging research in generative recommendation, foundation models, user modeling, generative retrieval, and representation learning, and lead promising approaches from research and prototypes into production.\nWhat Essential Skills You Will Need\nMaster's Degree in Computer Science, Machine Learning, Artificial Intelligence, Operations Research, or another quantitative field, or equivalent practical experience developing large-scale machine learning systems.\nAt least 7 years of relevant industry experience, including substantial experience designing and deploying production deep learning systems for recommendation, search, user modelling, NLP, or related applications at scale.\nExpertise and technical leadership in user modelling, recommendation systems, information retrieval, representation learning, or sequence modelling, with experience transforming large-scale behavioural data into representations that generalise across multiple downstream tasks (Theory and domain)\nExpertise with modern deep learning architectures, including Transformers and sequence-based models, with hands-on proficiency in frameworks such as PyTorch, TensorFlow.\nExperience designing large-scale ML systems, including distributed training, feature and embedding computation, real-time user representations, online inference, latency optimization, model monitoring, and retraining.\nProficiency in Python and experience with large-scale data processing technologies such as Spark, Scala, or equivalent distributed data systems\nExperience with experimentation and evaluation, including offline evaluation, A/B testing, metric design, and measuring the incremental impact of shared models and representations across heterogeneous downstream applications\nYou can bridge latest research and production systems — particularly in generative recommendation and foundation models — and identify where new modeling approaches provide meaningful advantages over established architectures\nYou can define technical direction in ambiguous problem spaces and influence senior engineers, data scientists, product managers, and leaders across organisational boundaries.\nYou may also place direct application via https://smrtr.io/BY9G4\nSkills\nGenerative Model, Machine Learning, Managing Diversity, Develop Recommendations, Large Scale Systems, Platform Management, Test Metrics, Model Training, Computer Science, Search Engine Ranking, Developing Frameworks, Recommender Systems, Organisational Leadership, Capability Analysis, Data Infrastructure, behavioural analytics, Evaluation Methodology, Ranking","description_format":"text","description_chars":5426,"description_truncated":false,"requirements":{"experience_years_min":7,"management_years_min":null,"team_size_min":null,"manages_managers":false,"education":null,"security_clearance":false,"languages":[]},"benefits":[],"hiring_locations":[{"name":"Singapore","iso":"SG","kind":"country"}],"hiring_excludes":[],"relocation_offered":false,"industries":[],"lifecycle":[{"event":"open","at":"2026-09-25T17:56:20Z"}],"visa":[],"liveness":{"score":24,"band":"cold","label":"Long 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