Intern Rewards & OD Data Scientist
Summary
This internship involves analyzing workforce data, modeling compensation trends, and evaluating organizational structures using Python, R, and SQL to enhance employee experience and performance within the People Department.
Job Description
Position Title: Intern, Rewards & OD Data Scientist
Department: PD (Rewards & Organisational Design)
Location: Kuala Lumpur - RedQ
We are looking for a driven and analytical Data Scientist Intern to join our People Department, Rewards and Organisational Design team. In this role, you will bridge the gap between people analytics and strategic HR decision-making. You will work closely with the team to analyze workforce data, model compensation trends, evaluate organisational structures, and leverage data science to enhance employee experience and performance across the airline.
Key Responsibilities
- People Analytics & Workforce Modeling: Support the development of predictive models and dashboards for employee turnover, retention drivers, talent acquisition, and workforce planning.
- Rewards & Compensation Analysis: Assist in benchmarking salary structures, analyzing market compensation data, and modeling the cost impact of merit increases, bonuses, and benefit programs.
- Organisational Design Insights: Analyze organizational metrics (e.g., span of control, layer depth, workforce efficiency) to support restructurings and organizational effectiveness initiatives.
- Data Cleansing & Pipeline Management: Aggregate, clean, and integrate data from various HR systems (such as Workday) to ensure data integrity for executive reporting.
- Ad-Hoc Data Requests: Build automated reports, visualizations, and data stories using tools like Python, R, SQL, Tableau, or Google Looker Studio to present findings to HR business partners.
Requirements
- Currently pursuing a Bachelor’s or Master’s degree in Data Science, Statistics, Computer Science, Economics, Mathematics, Human Resources, or a related quantitative field.
- Strong proficiency in data manipulation and analysis using Python or R, alongside proficiency in SQL.
- Familiarity with data visualization and dashboarding tools (e.g., Tableau, Power BI, or Looker Studio).
- Solid foundation in statistical analysis, regression modeling, and exploratory data analysis.
- Exceptional attention to detail with a high degree of discretion when handling confidential employee data.
- Passion for HR tech, people analytics, and improving organizational performance.
- High energy, adaptability, and an innovative mindset fitting the Allstar culture.