Grab Hiring! Full Time Senior Data Scientist (Consumer Experience) in - Ricebowl

Get to Know the Team

The Consumer Experience team aims to provide a great user experience across the app. The data science team works on problems ranging from ranking and recommendations to agentic LLM chatbots and content generation. We're a hands-on team interested in the end-to-end data lifecycle: from wrangling data to understanding the trade-offs between model complexity and deployment in production. We are looking for an experienced Data Scientist with an AI product mindset to help push the frontier of personalization. If you're passionate about solving complex problems with immediate real-world impact, we want you!

Get to Know the Role

You will focus on enhancing a communications targeting system by developing relevance ranking, translation models, and agentic marketing content generation projects. You will report to the Senior Data Science Manager and this role is based in Grab One North Singapore office. If you are ready to shape how millions of users interact with our platform, apply today!

The Critical Tasks You Will Perform

• You will enhance communication targeting systems by developing relevance ranking algorithms, translation models, and agentic marketing content generators.
• You will analyse quantitative and qualitative data to develop a deep behavioural understanding of our users and inform personalization strategies.
• You will collaborate with product, marketing, and engineering teams to manage the end-to-end lifecycle of designing, implementing, and deploying ML and LLM models.
• You will build and test robust models, develop data pipelines, and establish observability and evaluation frameworks for systems in production.
• You will leverage Generative AI (GenAI) and AI coding assistants to accelerate model development, automate data wrangling, and streamline your evaluation workflows.

What Essential Skills You Will Need

• At least 4 years of experience in data science or machine learning, supported by a Master's degree in Computer Science, Engineering, Mathematics/Statistics, or a related technical discipline.
• Proficiency in programming languages such as Python, R, or Java, along with experience in data pipeline development and ETL processes.
• Experience with predictive modelling algorithms (e.g., logistic regression, neural networks, decision trees, heuristic models) and their trade-offs in production.
• Hands-on experience with ML/DL frameworks and libraries, including Scikit-Learn, Pandas, XGBoost, TensorFlow, or PyTorch.
• Practical experience managing the end-to-end ML lifecycle, including feature selection, hyper-parameter optimization, and model validation.
• You have experience engaging with AI tools and emerging technologies to enhance productivity, improve workflows, and contribute new ideas.