Lead Data Scientist, People Analytics & Predictive Insights

GrabTaxi Holdings Pte. Ltd.

Petaling Jaya

On-site

MYR 150,000 - 270,000

Full time

2 days ago
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Benefits offered by this job

Life Insurance
Medical Insurance
GrabFlex
Parental leave
Birthday leave
Love-all-Serve-all volunteering leave
Grabber Assistance Programme
FlexWork arrangements

Job summary

Grab is seeking a Lead Data Scientist for the People Science team to shift the function from descriptive analytics to predictive insights and proactive decision support. You will own end-to-end delivery of people analytics projects and build self-service tools for non-technical users.

You will collaborate with the PDW team to improve data quality, define metrics, and drive data-driven decisions across People Operations, leveraging SQL, Python, and BI dashboards in a fast-paced environment.

Qualifications

  • Bachelor's or Master’s degree in Statistics, Mathematics, Computer Science, Economics or related field.
  • Minimum 5 years as a Data Analyst, Data Scientist, or Analytics Consultant.
  • Experience turning ambiguous questions into actionable recommendations.
  • Experience in People Analytics, HR data, or workforce research is a plus.

Responsibilities

  • Build predictive models and insight frameworks for People analytics.
  • Design self-service tools for managers to analyse data without mediation.
  • Partner with the People Data Warehouse (PDW) to improve data quality and access at scale.
  • Scope data collection needs and ensure privacy compliance.

Skills

SQL
Python
R
SAS
BI Dashboards
Storytelling
Stakeholder Engagement

Education

Quantitative degree

Tools

Tableau
Power BI
Data Warehouse

Job description

Grab is seeking a Lead Data Scientist for the People Science team to shift the function from descriptive analytics to predictive insights and proactive decision support. You will own end-to-end delivery of people analytics projects and build self-service tools for non-technical users.

You will collaborate with the PDW team to improve data quality, define metrics, and drive data-driven decisions across People Operations, leveraging SQL, Python, and BI dashboards in a fast-paced environment.

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