Data Analytics
People Research Scientist, People Analytics
Skills
1 month ago
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Important information
Contract type:
Permanent
Location:
Kuala Selangor, Selangor, Malaysia
Work mode:
Onsite
Published on:
22 September 2026
What they need
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 Research 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.
Work arrangementh: 5-day onsite.
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.
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