{"id":2516149,"url":"https://alion.io/job/grab-senior-data-scientist-search-recommendations","title":"Senior Data Scientist (Search & Recommendations)","company":{"id":158,"name":"Grab","domain":"grab.com","url":"https://alion.io/company/grab","size_band":"1001-5000","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"SmartRecruiters","truth_index":{"grade":"B","score":75,"open_postings":51,"ghost_share":0,"stale_share":1,"repost_share":0,"time_to_fill_p50_days":30,"computed_at":"2026-10-29T05:49:05Z"}},"role":"Data Science","role_family":"Data Science","seniority":"senior","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":null,"salary_estimate":{"min_usd":58000,"max_usd":118000,"period":"year","method":"role_seniority_country_remote_cell","sample_n":50},"experience_years_min":3,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"A/B Testing","optional":false},{"name":"Fine-tuning","optional":false},{"name":"Hugging Face","optional":false},{"name":"JAX","optional":false},{"name":"LLM","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":"TensorFlow","optional":false},{"name":"TorchServe","optional":false},{"name":"Transformers","optional":false}],"status":"live","first_seen_at":"2026-10-14T05:55:54Z","employer_posted_date":"2026-10-14","last_verified_at":"2026-10-29T07:29:04Z","board_verified":true,"closed_at":null,"days_open":15,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":15},"description":"About Grab and Our Workplace\nGrab 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.\n Get to Know the Team\nYou will join our Search and Recommendations team - join a group of machine learning engineers and data scientists who build the algorithms that help millions of users discover food, groceries, and services across Southeast Asia. We work with engineering, product, and business teams to turn data into features that directly impact how users navigate our platform.\nGet to Know the Role\nYou will report into the Senior Data Science Manager, and work onsite at Grab One North Singapore office. You will design and build machine learning systems that power search ranking and personalized recommendations at scale. Your work will span deep learning model development, LLM integration, and production deployment. You will measure your impact through offline evaluation metrics and online A/B test results that directly affect user engagement and business metrics.\nThe Critical Tasks You will Perform\nYou will design and implement deep learning algorithms for search ranking, session-based recommendations, and multi-objective personalization systems that serve millions of users daily.\n You will fine-tune and deploy Large Language Models (LLMs) to improve search query understanding and recommendation relevance.\nYou will lead offline evaluation design and online A/B testing to validate model performance, ensuring measurable improvements to user engagement before production release.\nYou will partner with software engineers to scale your models from prototype to production, including model serving optimization and latency requirements.\nYou will translate data insights into concrete product features by collaborating with product managers and business operations teams, defining requirements based on user behaviour analysis.\nYou will monitor model performance in production and implement retraining pipelines to maintain prediction quality as data patterns evolve.\n What Essential Skills You will Need\nTo perform the tasks above, you will need:\nMaster's in Computer Science, Operations Research, Statistics, or equivalent quantitative field, or equivalent practical experience building production ML systems at scale.\nAt least 3 years of experience building and deploying deep learning models for search, recommendation systems, or NLP applications in production environments.\nHands-on experience with Python and Scala to build data pipelines and model serving systems that process high-volume user interaction data.\n Proficiency in at least one deep learning framework (PyTorch, TensorFlow, or JAX) to implement neural network architectures for ranking and sequence modelling.\nExperience with LLM fine-tuning and deployment using frameworks such as Hugging Face Transformers or similar tools to adapt pre-trained models for search and recommendation tasks.\nDemonstrated experience with A/B testing frameworks and statistical evaluation methods to measure model impact on user behaviour metrics.\n Experience deploying models to production using ML serving infrastructure (such as TensorFlow Serving, TorchServe, or cloud-based ML platforms) and optimising for latency constraints.\n Life at Grab\nWe care about your well-being at Grab, here are some of the global benefits we offer:\nWe have your back with Term Life Insurance and comprehensive Medical Insurance.\nWith GrabFlex, create a benefits package that suits your needs and aspirations.\nCelebrate 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\nWe have a confidential Grabber Assistance Programme to guide and uplift you and your loved ones through life's challenges.\nWhat we stand for at Grab\nWe are committed to building an inclusive and equitable workplace that provides equal opportunity for Grabbers to grow and perform at their best. 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