Senior Data Scientist (Analytics)

Data Analytics; Singapore; On-site; SGD 70,000 - 90,000; Full time

Job summary

A leading analytics company in Singapore seeks an experienced analyst to work with cross-functional teams to design experiments and analyze user behavior. The ideal candidate will conduct A/B tests, derive insights from data, and provide strategic recommendations for product enhancements. Join us to optimize user engagement through data-driven decisions and innovative analytics techniques.

Qualifications

• Experience with A/B tests and experiment design.
• Strong analytical skills and understanding of user behavior.
• Ability to translate complex data into strategic recommendations.

Responsibilities

• Design and conduct A/B tests to evaluate product changes.
• Analyze results and provide actionable insights.
• Build and maintain dashboards for real-time performance tracking.

Skills

A/B testing

Data analysis

Statistical techniques

Machine learning

Data visualization

Job description

Get to Know the Team

Our Search and Personalisation Team focuses on advancing scalable machine learning and experimentation frameworks that power search relevance, ranking, and recommendations across Grab. By leveraging cutting‑edge analytics and statistical methods, we continuously optimize how users connect with merchants, services, and content.

Get to Know the Role

In this role, you will work closely with product managers, data scientists, engineers and product designers to define hypotheses, design experiments, and deeply understand user needs, pain points, and business goals. You will act as a strategic partner throughout the product development lifecycle — offering analytical support from ideation to execution—and help prioritize features through data‑driven insights. You will be based in Singapore and reporting to Head of Analytics.

The Critical Tasks You Will Perform

• Design and run A/B tests and quasi‑experiments to evaluate the impact of product changes on key metrics like engagement, retention, and conversion.
• Analyze experiment results and generate actionable insights to guide product improvements.
• Conduct deep‑dived user behaviour analyses using statistical techniques and machine learning to uncover trends and root causes.
• Translate complex data into clear, strategic recommendations for product enhancements.
• Build and maintain intuitive dashboards to track product and feature performance in real time.
• Visualize data effectively to highlight trends, anomalies, and opportunities, enabling data‑driven decisions across teams.