Get to Know the Team

The GrabFood Analytics team is part of ACE Analytics, which covers GrabFood, GrabMart, GrabExpress and OmniCommerce. We are the product analytics partners to the GrabFood product organisation across six Southeast Asian markets. Each analyst owns one or two product problem spaces end-to-end. They define the metrics that matter, design and read the experiments behind every launch, and run the deep dives that decide what gets built next. We work AI-first: analysts build and share reusable AI workflows that take on the repetitive parts of the job, so our time goes to judgement and product thinking. This is a new seat, created to take on additional product problem spaces.

Get to Know the Role

Reporting to the Senior Analytics Manager, you will be the analytics owner. You will also be the advisor for one to two GrabFood product problem spaces. These problem spaces may include, for example, ordering experience and conversion, merchant discovery and content, delivery reliability and demand shaping, or affordability and promotions. You will work directly with the product manager, designers, engineers and data scientists for that space, most of whom are based in Singapore, and with country teams across the region.

This is a senior individual-contributor role. You set the metrics. You design an experiment and read it. You make the ship, iterate or stop recommendation and hold it when the data says so. You decide what to prioritise when several partners need you in the same week.

This is a product analytics role, not a machine-learning role: your time goes to metrics, experiments, root-cause analysis and product decisions, not to model building.

We base this role in Petaling Jaya and will require you to work onsite.

The Critical Tasks You Will Perform

• You will define the metrics for your problem space: the primary metric at the exact step a feature changes, the leading and lagging indicators around it, and the guardrails that catch the failure modes.
• You will design and analyse controlled experiments with your product manager: hypothesis, randomisation unit, success metric, sample size and duration, guardrails, and the checks that keep a result honest. You will turn results into a clear ship, iterate or stop recommendation.
• You will diagnose metric movements systematically. This will involve, locating the movement, decomposing it, cutting it by funnel step, segment, platform, and market. After that, ruling out tracking and data-quality causes. Finally, explaining it why.
• You will size opportunities and run proactive deep dives into consumer, merchant and driver-partner behaviour that shape the roadmap rather than report on it.
• You will oversee the data specifications and instrumentation for new features with engineering, so the data exists to measure what you planned to measure.
• You will build the dashboards and certified metrics that give the product team reliable self-serve visibility.
• You will build AI-assisted analytics workflows for yourself and the team, validated against raw data and business logic, and share what works.
• You will improve on experimentation and analytical rigour across the problem spaces you touch, and coach junior analysts as the team grows.

What Essential Skills You Will Need

• At least 4 years in analytics or quantitative roles, with at least 2 years of experience where you owned the metrics fo