Assistant Manager Data Science (Category Optimization & Allocation)

Key Responsibilities:

• Prediction and Forecast Models
  Build and maintain forecasting models to support business planning and decision-making

• Model Evaluation
  Evaluate model accuracy using appropriate metrics and continuously improve model performance

• What-if Simulation Apply strong business understanding to define realistic scenarios, assumptions and constraints. Evaluate not only statistical/model outcomes, but also the commercial and operational impact of proposed changes.

• Allocation Optimization
  Balance technical optimization with practical business constraints such as stock availability, demand, store capacity, and operational feasibility. Challenge model recommendations when results do not align with business reality.

• Dashboarding and Analytics
  Create and maintain impactful analytics that drive business decisions across various platforms (e.g., dashboards)

• Data & Collaboration
  Work with data stakeholders to ensure reliable data pipelines and translate business requirements into analytical solutions

• Stakeholder Management
  Communicate and collaborate with stakeholders from diverse backgrounds (e.g., IT and business)
  Translate requirements into clear and understandable terms for all relevant parties

• Project Management (good to have)
  Manage end-to-end project delivery, including defining scope, timelines, priorities, and stakeholder engagement

• Decision Making
  Evaluate data and model outputs to make informed decisions. Consider business impact, risks and feasibility, and plan and execute agreed initiatives effectively.

• Business Understanding & Problem Solving
  Understand business needs and key retail operations. Translate business problems into clear analytical questions and measurable KPIs, and identify suitable approaches to solve them.

• Any Other Tasks as Assigned

Requirements:

• Minimum 3-5 years of relevant experience in a similar field
• Possess at least a Bachelor’s Degree in Computer Science, Data Science, Information Technology, or an equivalent combination of education and practical experience
• Strong proficiency in Python (e.g., libraries such as pandas, sklearn) and SQL
• Hands-on experience in time series forecasting and predictive modeling
• Excellent analytical and problem-solving skills with a data-driven mindset
• Solid understanding of Machine Learning concepts and techniques
• Proven experience in project management, including planning, execution, and delivery (good to have)
• Strong stakeholder management skills, with the ability to engage and collaborate across diverse teams (good to have)
• Demonstrated critical and creative thinking abilities
• Effective problem-solving skills with the ability to develop practical and innovative solutions

As we continue our rapid expansion across the Klang Valley and other states in Malaysia, we're seeking passionate and qualified Malaysian to join our growing team.

In 2024, we recorded an Employee Satisfaction Score of 91% - a meaningful benchmark that reflects our ongoing commitment to creating a workplace where people thrive.

MR D.I.Y. is a home-grown enterprise with over 1,300 stores across Malaysia and Brunei. The home improvement retailer has dedicated to make a positive difference in the lives of its valued customers by offering convenience at all its stores nationwide and online at mrdiy.com.my

All MR. D.I.Y. stores are managed directly and the retailer often works in collaboration with owners of shopfront properties or owners of malls. MR. D.I.Y. stores offer a wide selection of SKUs across five major categories, namely hardware; household and furnishing; electrical; stationery and sports equipment products; and others (comprising toys, car accessories, jewellery, cosmetics, food and beverage items, as well as health and personal care).

The Company strives to put its customers first by operating an innovative business that is flexible when it comes to providing a wide variety of products, good quality and value-for-money, holding true to the Company’s motto of “Always Low Prices”.