Additionalinformation

Additional Information

Life at Grab

We care about your well-being at Grab, here are some of the global benefits we offer:

• We have your back with Term Life Insurance and comprehensive Medical Insurance.
• With GrabFlex, create a benefits package that suits your needs and aspirations.
• Celebrate moments that matter in life with loved ones through Parental and Birthday leave, and give back to your communities through Love-all-Serve-all (LASA) volunteering leave
• We have a confidential Grabber Assistance Programme to guide and uplift you and your loved ones through life's challenges.
• Balancing personal commitments and life's demands are made easier with our FlexWork arrangements such as differentiated hours

What We Stand For At Grab

We are committed to building an inclusive and equitable workplace that provides equal opportunity for Grabbers to grow and perform at their best. We consider all candidates fairly and equally regardless of nationality, ethnicity, race, religion, age, gender, family commitments, physical and mental impairments or disabilities, and other attributes that make them unique.

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Company Description

About Grab and Our Workplace

Grab is Southeast Asia's leading superapp. From getting your favourite meals delivered to helping you manage your finances and getting around town hassle-free, we've got your back with everything. In Grab, purpose gives us joy and habits build excellence, while harnessing the power of Technology and AI to deliver the mission of driving Southeast Asia forward by economically empowering everyone, with heart, hunger, honour, and humility.

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Job Description

Get to Know the Team

The People Science team, within Grab's Office of Organisational Capabilities, turns people data, research, and AI into better organisational decisions. We are building a user-centric intelligence capability that helps Grabbers, managers, People teams, and business leaders understand what is happening, identify what matters, and take effective action.

Get to Know the Role

As Data Scientist, People Analytics you will apply strategic consulting, applied research, and structured problem-solving to complex people and organisational challenges. You will build AI systems and agents that automate People Science workflows, develop an organisational listening engine that turns signals into action, and advise People and business leaders on real problems. This is a hands-on role requiring research rigour, analytical judgement, and user-centric product thinking.

You will report to the Head, People Science.

The Critical Tasks You Will Perform

• Build an organisational listening and action engine using employee listening, workforce, behavioural, and operational data to identify signals, diagnose root causes, and guide action.
• Build user-centric AI systems and agents that automate People Science workflows, from data discovery and analysis to hypothesis testing, programme evaluation, insight generation, and recommendations.
• Conduct applied organisational research using qualitative and quantitative methods, including surveys, interviews, experiments, and mixed-method approaches.
• Design hypotheses and evaluate People programmes or interventions using appropriate research, experimental, or quasi-experimental methods.
• Act as a strategic advisor to People and business leaders by framing ambiguous problems, conducting analysis, evaluating options, and translating evidence into practical decisions.
• Democratise people data through accessible AI agents, self-service tools, and data products that help non-technical users make better decisions.

Qualifications

What Essential Skills You Will Need

• 8 - 12 years of experience in strategic consulting, applied research, organisational research, decision science, analytics, or a related field, with hands-on end-to-end problem solving.
• Experience advising senior stakeholders by defining ambiguous problems, diagnosing root causes, evaluating options, and translating evidence into practical decisions.
• Strong applied research capability across qualitative and quantitative methods, including research design, hypothesis development, surveys, interviews, experiments, and mixed-method approaches.
• Practical knowledge of programme evaluation, experimental design, causal or quasi-experimental analysis, and the ability to interpret evidence and its limitations.
• Experience synthesise data, research findings, and user perspectives into clear recommendations.
• Working proficiency in at least one analytical language, such as SQL, Python, or R, with the ability to conduct and interpret analysis.
• Experience engaging with AI tools and emerging technologies to improve research, analysis, workflows, and decision support, with an understanding of responsible AI, privacy, and bias considerations.

Good To Have

• Experience in People Analytics, organisational psychology, behavioural science, workforce strategy, or social research.
• Experience building or prototyping AI systems, AI agents, LLM-enabled workflows, or analytical automation.
• Experience with employee listening, behavioural interventions, productivity measurement, programme implementation, or organisational change.