Get to Know the Team

You'll be part of the SNP Data Science Personalization team, an established group dedicated to enhancing personalization experiences for Grab Food/Mart/Transport. We aim to develop cutting-edge Deep Learning models to deliver best user experiences. Our team comprises passionate Data Scientists with various expertise. If personalization and recommendation challenges excite you, we'd love to have you join us!

Get to Know the Role

As a Senior Data Scientist, you will lead the solution and implementation of context-based Transport user understanding, including but not limited to feature engineering for Transport user profiles of price/promo/taxi type preferences/etc. in the current context (e.g. location/time/funnel). In addition, you will lead the solution and implementation of enhanced Transport personalization and Taxi Type ranking (include model training and model serving) for Grab's Mobility vertical with auto-adaptive capabilities. Your important work contributes significantly to Grab's growth.

You will be based onsite at Grab Singapore One North office and report to the Senior Data Science Manager.

The Critical Tasks You Will Perform

• You will process large-scale datasets for model development and training.
• You will design and implement efficient, scalable machine learning and deep learning algorithms.
• You will evaluate how algorithms perform to improve relevance and personalization.
• You will deploy models to production environments, focusing on robustness and maintainability.
• You will run A/B tests to assess model performance, troubleshoot issues, and pinpoint opportunities for improvement.
• You will keep up with recent advances in User Understanding, Recommendation ranking model, and LLMs.
• You will work closely with backend engineers, product managers, analysts, and UX designers.

What Essential Skills You Will Need

• You have a Bachelor's degree in Computer Science, Electrical/ Computer Engineering, or a related technical field.
• You have at least 3 years of experience applying deep learning in domains like User Understanding, Recommendation Systems, or LLMs.
• You can develop and deploy large-scale machine learning solutions.
• You can translate requirements into technical solutions.
• You have expertise in frameworks like TensorFlow or PyTorch.
• You have software development abilities in Python.