- Job Type: Full-Time
- Function: Data Science
- Industry: Transportation
- Post Date: 10/10/2024
- Website: grab.com
- Company Address: 3 Media Close, Grab HQ #01-03/06, Singapore, Singapore 138498, SG
About Grab
Grab is Southeast Asia’s leading superapp, offering a suite of services consisting of deliveries, mobility, financial services, enterprise and others. Grabbers come from all over the world, and we are united by a common mission: to drive Southeast Asia forward by creating economic empowerment for everyone.Job Description
The Deliveries Analytics team is the analytics and data powerhouse behind Grab's fastest-growing segments: GrabFood, GrabMart. Here, innovation meets action. We're not just a team; we're trailblazers, committed to solving the most pressing challenges for our consumers, driver-partners, and merchant-partners leveraging data. From revolutionizing the consumer order experience to enhancing platform reliability, we strive to make Grab the first choice, every time.
Get to Know the Role
You will report to the Product Analytics Manager II, ACE and you'll have the unique opportunity to collaborate across disciplines (Product, Business, Engineering, Design, Data Science) to transform data into dynamic solutions. Your insights will directly contribute to developing groundbreaking products and initiatives, setting new benchmarks for excellence. This isn't just any role; it's a chance to make a tangible impact on millions of lives every day.
The Critical Tasks You Will Perform
- You will understand our requirements and outcomes to ensure data-driven decision-making.
- You will conduct tailored analyses for specific products and operations, define critical business metrics, track them rigorously, and recommend continuous improvements.
- You will frame business scenarios and propose features that impact critical business processes and decisions.
- You will transform requirements into concise insights through reports, presentations, and dashboards, and consolidate data from multiple sources to create comprehensive views for decision-making.
- You will develop data pipelines and custom data science models to solve identified problems.
- You will launch A/B tests, analyze the results, and provide recommendations based on your findings.