Lead Data Scientist, People Science

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

Job summary

Grab is seeking a Lead Data Scientist for the People Science team within the Office of Organisational Capabilities. The role focuses on shifting from descriptive analytics to predictive insight, designing new data sources and self‑service tools for managers and leaders, and partnering with the PDW to scale data access and quality.

The candidate will own end‑to‑end delivery across people analytics, building predictive models and insight frameworks, and shaping data‑driven interventions with

Responsibilities

• Delivering predictive and forward‑looking insight
• Transform complex, multi‑source people datasets into clear, decision‑ready narratives for senior stakeholders
• Design and measure the impact of data‑ and science‑backed behavioural interventions
• Build and maintain People metrics, scorecards, and dashboards for end‑to‑end employee lifecycle
• Design and ship self‑service tools and workflows with internal platforms such as Valet and Cortana
• Identify gaps in data and design new collection mechanisms to fill them
• Partner with the People Data Warehouse (PDW) team to improve data access at scale
• Apply a structured consultative approach to People problems and deliver measurable impact

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 Lead 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 be working on reporting but will 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 escalates.
• 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.