Data Scientist (Analytics), Financial Services

Get to Know the Team

Financial Services (FS) Analytics partners with Product, Business, Risk, Design and Engineering across Lending, where we aim to be the biggest FinTech Lender in the region. We sit inside the decisions, not downstream of them. You'll learn from senior analysts who have done this across Grab, and you'll get ownership early.

Most analytics roles hand you a dashboard queue, or ask you to build pipelines. We instead will hand you questions about how millions of people borrow, pay and save.

Grab Financial Services runs payments, lending, insurance and the digital banks as one team. We serve people across Southeast Asia that traditional banks often overlook. Your work will shape products they use every day.

You'll also learn analytics the way it's done now, in an AI-first world. Our analysts work with AI agents every day. Agents take the first pass at queries and analysis. You'll learn to direct them, check them and build with them. Few teams anywhere work this way yet!

Get to Know the Role

You will use data to understand user needs and be the de-facto Voice of the Customer (users, driver-partners, merchants, agents) across Lending. You will use data to unveil insights to help scale our products. You will promote data-driven decision-making within Financial Services and partner with Product Managers, Business Owners, UX Designers, and Engineers to design analytical projects that inform the Product roadmap. You will provide expertise and produce data-driven hypotheses to solve important Product and Business problems, and guide our Financial Services' strategies forward.

You will report into the Senior Analytics Manager, Payments of Lending and work onsite at our office in Singapore, Grab HQ One-North.

The Critical Tasks You Will Perform

• Deliver reliable analysis: Take clearly defined problems and deliver accurate answers.
• Learn the experimentation craft: Help design, run and read A/B tests with support from senior analysts. Build your judgement on how to interpret experiment results.
• Reporting: Build and maintain dashboards, metric definitions and the data your partners rely on. Accuracy is non-negotiable.
• Work AI-first: Use AI tools every day to write SQL and Python, explore data and speed up your work. Check what they give you before anyone else sees it. Automate the repetitive parts of your job.
• Keep partners in the loop: Share progress, changes and findings early. Explain what the data says in plain language and with enough context to act on.
• Manage your growth: Ask for feedback, act on it and pick up our best practices quickly.

Function: Analyst
Experience Level: Associate