Assistant Manager Data Science (Category Optimization & Allocation)

MR.DIY Group (M) Berhad; Seri Kembangan; Hybrid; MYR 60,000 - 120,000; Full time

Job summary

MR.DIY Group (M) Berhad is seeking an experienced Data Analytics professional to drive forecasting, demand planning, and inventory optimization across a multi-store retail network. The role emphasizes building robust models, delivering actionable dashboards, and collaborating with IT and operations teams.

Candidates should have 3+ years in data analytics or related fields, strong Excel/Python/SQL skills, and hands-on experience with time series forecasting and analytics for retail.

Qualifications

• Minimum 3 years of relevant experience in data analytics, business analytics, inventory planning, supply chain analytics, retail analytics, or a similar field.
• Bachelors 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.

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: Define realistic scenarios, assumptions and constraints; evaluate commercial and operational impact.
• Allocation Optimization: Balance technical optimization with stock availability, demand, store capacity and feasibility.
• Dashboarding and Analytics: Create analytics that drive business decisions across 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 with IT and business stakeholders; translate requirements clearly.
• Project Management: Manage end-to-end project delivery including scope, timelines, priorities and engagement.
• Decision Making: Evaluate data and model outputs to make informed decisions considering risks and feasibility.
• Business Understanding & Problem Solving: Translate business needs into measurable KPIs and analytical approaches.
• Any Other Tasks as Assigned

Skills

Excel

Python

SQL

Time series forecasting

Forecasting models

Education

Bachelors Degree in Computer Science, Data Science, IT, Statistics, Mathematics, Business Analytics or SCM

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.