Responsibilities

Drive business intelligence function at group HR-Centre of Excellence (COE), formulate cluster-wide manpower analytics initiatives and parameters, and monitor the implementation of HR Analytics
Leveraging on data to gain insights that will serve as inputs for developing effective HR initiatives to meet the broad objectives of the organization. This role will also be responsible for day-to-day operations of servicing the needs of various stakeholders for HR reporting, dashboard, predictive analytics (include scenario simulation) and perform data analytics from MyHR (Successfactor) for Head Office and Centralized Group level regulatory reporting, data harmonization/alignment and design of Advance reports.
Develop and implement data analytics strategies aligned with business goals
Lead and manage a team of data analysts or scientists
Collaborate with other department heads to identify data-driven opportunities
Oversee data collection, creation of warehouse, and quality assurance processes
Ensure data security and compliance with relevant regulations
Guide the development of advanced analytics models and methodologies
Translate complex data findings into actionable business insights
Drive data-driven decision making across the organization
Oversee the development and maintenance of data infrastructure, establish CI/CD practices for deploying analytics models and dashboards reliably and securely
Reporting and Communication:
Present findings and recommendations to senior management and stakeholders
Develop and maintain dashboards and reporting systems

Requirements

Degree or higher in a relevant field such as Data Science, Statistics, Computer Science, or Business Analytics
At least 8-10 years of experience in manpower planning analytics and modelling with strong ability to summarise, visualise, and present data for decision making.
Good understanding of HR systems (especially SuccessFactors) and business intelligence databases.
Strong leadership and team management abilities
Excellent communication and presentation skills
Strategic thinking and problem-solving capabilities
Business acumen and ability to translate data insights into business value

Technical Skills:

Proficiency in data analysis tools and programming languages (e.g., Python, R, SQL) and cloud-based data architecture (AWS S3, Databricks, Spark and Delta lake)
Knowledge (hands-on) on of machine learning, CI/CD pipelines and statistical modeling techniques, including advanced Excel skills
Strong data visualization tools (e.g., Tableau, Power BI) and PowerPoint presentation skill