Assistant Manager Data Science (Category Optimization & Allocation)

MR DIY Malaysia

Seri Kembangan

On-site

MYR 90,000 - 130,000

Full time

29 hours ago
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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

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 data analytics, business analytics, inventory planning, supply chain analytics, retail analytics, or a similar field.
  • Possess at least a Bachelor’s Degree in Computer Science, Data Science, Information Technology, Statistics, Mathematics, Business Analytics, Supply Chain Management, or an equivalent combination of education and practical experience.
  • Strong proficiency in Microsoft Excel, Python and SQL, with hands-on experience in data manipulation, analysis, and automation using tools/libraries such as pandas and scikit-learn.
  • Hands-on experience in time series forecasting, demand forecasting, predictive modeling, or other statistical/data-driven modeling techniques.
  • Strong understanding of retail operations, store allocation, inventory management, replenishment, and demand planning.
  • Strong analytical, critical-thinking, and problem-solving skills, with the ability to translate data insights into practical business solutions.
  • Proven experience in project planning, execution, coordination, and delivery, with the ability to manage multiple tasks and timelines.
  • Strong stakeholder management and communication skills, with the ability to work effectively with business, IT, operations, and other cross-functional teams.
  • Ability to independently identify business problems, analyze root causes, propose solutions, and drive implementation.
  • Knowledge of Machine Learning concepts and techniques is an advantage.

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”.

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