Senior Data Scientist (Analytics)

Data Analytics; Singapore; On-site; SGD 100,000 - 125,000; Full time

Job summary

A leading company in analytics based in Singapore is seeking a strategic partner in its analytics team. The role involves working closely with product managers and engineers to optimize user engagement and product performance through data-driven insights and statistical analyses. Candidates should have experience in A/B testing and data visualization.

Qualifications

• Strong analytical skills and experience in using statistical techniques.
• Proficiency in designing and analyzing A/B tests.
• Experience in building and maintaining dashboards.
• Ability to translate complex data into strategic recommendations.

Responsibilities

• Design and run A/B tests to evaluate product changes.
• Analyze experiment results for product improvements.
• Conduct deep-dive analyses of user behavior.
• Build dashboards to track product performance.
• Visualize data to highlight trends and anomalies.

Skills

Machine learning

Statistical analysis

A/B testing

Data visualization

User behavior analysis

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-dive user behavior 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.