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 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.