Senior Data Scientist, People Science

Data Analytics; Selangor; On-site; MYR 180,000 - 240,000; Full time

Job summary

Grab in Malaysia is seeking a Senior Data Scientist to advance the People Science effort from descriptive dashboards toward predictive insight, enabling leaders to act on data-driven recommendations. You will own end-to-end analytics across people data: building predictive models, designing self-service tools, and partnering with the PDW team to improve data quality and access at scale.

This role requires strong stakeholder engagement, product thinking, and consultative judgement to deliver

Qualifications

• Experience delivering predictive models and insight frameworks for a large organization.
• Ability to design and ship self-service analytics tools for non-technical users.
• Strong partner­ship with data teams to improve data quality and access at scale.

Responsibilities

• Delivering predictive and forward-looking insight.
• Transform complex, multi-source people datasets into clear, decision-ready narratives for leaders and stakeholders.
• Design and measure the impact of data-driven interventions that shape organisational behavior.

Skills

Predictive modeling

Data storytelling

Stakeholder consulting

Cross-functional collaboration

Self-service analytics

Tools

Valet

Cortana

PDW

Job description

The People Science (PSI) team that is part of the Office of Organisational Capabilities (OCO) team. The OCO team works at the intersection of People Operations (Pops), Corporate Real Estate and Security (CREST), and Grabber Technology Services (GTS): the three domains that shape how every Grabber performs day to day, covering their people experience, physical environment, and digital tools.

Within OCO, the People Science (PSI) team is Grab's internal capability for turning people data into strategic advantage. PSI is evolving: moving beyond dashboards and retrospective reporting toward predictive insight, democratised self-service analysis, and the design of new data sources where they do not yet exist. Our work directly advances Grab's People North Star, which is to increase productivity advantage while optimising People Team costs.

You will report to the Head, People Science.

Get to Know the Role

As a Senior Data Scientist on the People Science team, you will play a hands-on role in shifting how Grab's People function operates: from describing what happened to predicting what will happen and recommending what to do about it now.

You will own end-to-end delivery across people analytics: building predictive models and insight frameworks, designing and shipping self-service tools that allow managers and leaders to analyse people data independently, identifying gaps in existing data and designing new collection mechanisms, and partnering with the People Data Warehouse (PDW) team to improve data quality and access at scale.

You will not working on reporting but to focus on insight and product that requires equal parts analytical rigour, product instinct, and consultative judgement. You will define what to measure, not just how to measure it to solve end-to-end problems while collaborating closely with cross-functional partners.

The Critical Tasks You Will Perform

The work will be dynamic and challenging, requiring a combination of technical depth, product thinking, and stakeholder consulting skills. You will be responsible for:

Delivering predictive and forward-looking insight

• Build and maintain analytical models that generate proactive signals across the People North Star, including flight risk, skill growth, disengagement indicators, and People Team cost-to-serve, enabling the People function to act before issues elevate.
• Transform complex, multi-source people datasets into clear, decision-ready narratives for People Operations leaders and senior stakeholders.
• Design and measure the impact of data- and science-backed behavioural interventions that shape Grabber behaviours at scale (e.g. embedding meeting-hygiene practices and nudge design grounded in behavioural research).

Democratising people data and analysis

• Build and maintain People metrics, scorecards, and dashboards across the employee lifecycle, covering engagement, productivity, skills, and cost, designed for usability by non-technical audiences and not just analytical accuracy.
• Design and ship self-service tools and workflows, including integrations with internal platforms such as Valet and Cortana, that enable managers and leaders to conduct their own people analysis without PSI mediation.
• Transform existing People assets (e.g. the People Impact Card) from static summaries into automated, insight-driven outputs with actionable recommendations and just-in-time nudges.

Designing new data sources

• Identify gaps where existing people data is insufficient to answer critical workforce questions, and design new data collection mechanisms to fill them: not just improving what exists, but building what is needed.
• Scope data requirements, guide toward optimal data models, and run user testing to ensure new sources are usable, sustainable, and privacy-compliant.
• Partner with the People Data Warehouse (PDW) team to solve for upstream data access design, hygiene, and automation in a scalable way.

Consultative business partnering

• Apply a structured consultative approach to People problems: scope the question, develop hypotheses, mine data, and deliver recommendations with measurable impact.
• Partner with People Operations teams as an embedded analytics advisor, defining success metrics, responding to ad hoc insight requests, and connecting analysis to ongoing People initiatives.
• Support robust data-repository creation by scoping requirements, guiding toward optimal data models, and running user testing.