AI-Driven Data Scientist for Fintech Lending

Grab; Singapore; On-site; SGD 60,000 - 100,000; Full time

Benefits offered by this job

Term Life Insurance

Medical Insurance

GrabFlex benefits

Parental leave

Birthday leave

LASA volunteering leave

Grabber Assistance Programme

FlexWork hours

Job summary

Grab Financial Services seeks an early-career analytics professional in Singapore to answer real questions about how millions borrow, pay, and save. You’ll partner with Product, Business, Risk, Design and Engineering to shape the Lending roadmap and own data-driven hypotheses with guidance from senior analysts.

You’ll use data to understand user needs, be the Voice of the Customer across Lending, and collaborate to inform product decisions using SQL, Python and AI-assisted tools.

Qualifications

• A degree in Statistics, Economics, Mathematics, Engineering, Computer Science or a related field.
• Solid SQL and working Python.
• A good grasp of statistics and hypothesis testing. Hands-on A/B testing experience is a plus.
• You already work with AI.
• Clear communication. You can explain an analysis to someone who isn't a data person.
• Curiosity and a fast learning curve.

Responsibilities

• Deliver reliable analysis and provide answers with minimal guidance.
• Learn the experimentation craft and help design, run and read A/B tests with guidance.
• Reporting: build and maintain dashboards, metric definitions and data dependencies.
• Work AI-first: write SQL and Python with AI tools; validate outputs before sharing.
• Keep partners in the loop: explain data with context for action.
• Own your growth: seek feedback and adopt best practices quickly.

Skills

SQL

Python

Statistics

Communication

Curiosity

AI tools

A/B testing

Education

Statistics/Economics/Math/Engineering/CS degree

Tools

Visualization tool

Job description

Grab Financial Services seeks an early-career analytics professional in Singapore to answer real questions about how millions borrow, pay, and save. You’ll partner with Product, Business, Risk, Design and Engineering to shape the Lending roadmap and own data-driven hypotheses with guidance from senior analysts.

You’ll use data to understand user needs, be the Voice of the Customer across Lending, and collaborate to inform product decisions using SQL, Python and AI-assisted tools.