Grab Hiring! Full Time Senior Data Scientist, Ads - Demand Optimization in - Ricebowl

Get to Know the Team

Join our Ads and Demand Optimization Team, sitting at the intersection of machine learning, economics, and engineering. We design algorithms ensuring the right ads and promotional incentives reach the right audience. We optimise ads inventory and promotional spend to maximise Return On Investment (ROI) for merchants, users, and the platform. We focus on architecting the "brains" behind the system—solving complex marketplace challenges.

Get to Know the Role

We are looking for a Senior Data Scientist (G4) to bridge ads ranking and demand personalization. You'll develop algorithmic frameworks that shape user journeys, govern ads auctions, and allocate promotional budgets.

You'll report into the Data Science Manager II and based onsite at Grab One North Singapore office.

The Critical Tasks You Will Perform

• Design Optimization Frameworks: Develop data science methodologies for ad ranking and automated promo assignment.
• Lead Causal Inference: Deploy uplift models and causal inference frameworks to maximise promotional incrementality.
• Optimise Auctions: Improve ads auction mechanics and budget allocation to balance ecosystem health and platform ROI.
• Experimentation and Metrics: Design frameworks (A/B testing, switchback, bandits) evaluating CTR, CVR, and incremental GMV.
• Collaborate: Partner with Product and Engineering to translate marketplace challenges into clear data science roadmaps.

What Essential Skills You Will Need

• Qualification: Bachelor's Degree in Computer Science or related fields
• Experience: At least 4 years as a Data Scientist in ads ranking, recommendation, uplift modelling, or marketplace optimization.
• Methodology: Expertise in causal inference, uplift modelling, experimental design, or ads auction theory.
• Foundations: statistical modelling, machine learning, and mathematical optimization foundations.
• Tools: Proficiency in Python, SQL, and distributed data frameworks like Spark for large-scale datasets.
• Communication: Ability to translate complex concepts and bring structural clarity to open-ended product problems.