Lead Data Scientist, People Analytics

Role Overview

As a Lead 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.

What You Will Do

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.

Why It Might Be a Fit

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.

Requirements

• 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.

Benefits

• Term Life Insurance
• Medical Insurance
• GrabFlex
• Parental and Birthday leave
• Love-all-Serve-all (LASA) volunteering leave
• Grabber Assistance Programme
• FlexWork arrangements