Category Forecast & Allocation Manager

MR DIY Malaysia; Seri Kembangan; On-site; MYR 90,000 - 130,000; Full time

Job summary

MR D.I.Y. Malaysia is seeking a data analytics professional to build forecasting models, evaluate accuracy, and support business planning across retail operations. You will translate data into actionable insights to drive store performance nationwide.

The ideal candidate has 3–5 years of relevant experience, a Bachelor's degree in a related field, and strong Excel, Python, and SQL skills with time-series forecasting experience.

Qualifications

• 3–5 years of data analytics, inventory planning, or retail analytics experience.
• Bachelor’s degree in CS/Data Science/IT/Statistics/Math/Business Analytics/Supply Chain.
• Strong Excel, Python and SQL skills with data manipulation and automation.
• Hands-on time series forecasting and predictive modeling experience.
• Understanding of retail operations, inventory, replenishment and demand planning.
• Ability to translate data insights into practical business solutions and manage multiple tasks.

Responsibilities

• Build forecasting models to support business planning.
• Evaluate model accuracy using appropriate metrics and improve performance.
• Apply What-if scenarios to assess commercial impact.
• Balance optimization with stock availability and store constraints.
• Create analytics and dashboards to drive decisions.
• Ensure reliable data pipelines and translate business needs into analytics.
• Collaborate with IT and business stakeholders across functions.

Skills

Excel

Python

SQL

Time series forecasting

Demand planning

Data analysis

Stakeholder management

Project coordination

Pandas

scikit-learn

Education

Bachelor’s Degree in Computer Science

Tools

pandas

scikit-learn

Job description

MR D.I.Y. Malaysia is seeking a data analytics professional to build forecasting models, evaluate accuracy, and support business planning across retail operations. You will translate data into actionable insights to drive store performance nationwide.

The ideal candidate has 3–5 years of relevant experience, a Bachelor's degree in a related field, and strong Excel, Python, and SQL skills with time-series forecasting experience.