Senior Data Scientist (Analytics) - Demand

Get to know the Team

The Demand Analytics team turns data into growth—strengthening Grab's market leadership, optimizing product and promo performance, unlocking new demand through lifecycle and gamified experiences, scaling cross-vertical incentives and rewards, and partnering with product and business teams to pilot and scale high-ROI initiatives.

Get to know the Role

As a Senior Data Scientist for Demand team, you will be the analytical backbone of our growth strategy. You'll work with Product, Business, and Engineering teams to understand consumer behavior, identify market opportunities, and track the impact of our demand-generation efforts. Your role is to turn massive datasets into a roadmap for sustainable growth and competitive advantage.

You will reporting to our Analytics Manager and base onsite in our Petaling Jaya office.

The Critical Tasks You Will Perform

• Identify Strategic Opportunities: Deep-dive into existing data to recommend product ideas that either solidify our current market share or unlock entirely new growth levers.
• Lead Experimentation: Design and propose robust experimentation strategies for new and exploratory features, analyzing results to provide clear "go/no-go" recommendations.
• Leverage AI for Insights: Utilize Generative AI and LLM-based tools to accelerate insight generation, automate root-cause analysis, and build intuitive, natural-language interfaces for complex data inquiries.
• Master Data Storytelling: Use visualization techniques and dashboards to present complex insights to non-technical audiences, influencing regional product roadmaps.
• Develop Scalable Frameworks: Identify recurring demand-side problem statements and build generalized analytical solutions to solve them efficiently at scale.
• Own Data Integrity: Design frontend and backend data specs for new demand features, collaborating with engineering to ensure high-quality data collection.
• Mentor and Role-Model: Support the professional development of junior team members while maintaining high standards of rigor in measurement, experimentation, and analysis.