Key Responsibilities
1. Demand Forecasting & Budget Ownership
- Lead annual budgeting and rolling 6-12M forecasts by integrating historical sales, promotions (Animations), and launch plans, leveraging machine learning models to achieve target accuracy (KPI: forecast accuracy > 70% in country level).
- Develop automated dashboards (Power BI/Tableau) for real-time SKU-level forecast deviation tracking.

2. Procurement & Inventory Control
- Design purchase strategies (regular/promotional stock) to balance inventory turnover and stock-out risks.
- Manage product lifecycle (Phase-in/Phase-out) and aging stock mitigation plans.

3. End-to-End Supply Chain Collaboration
- Facilitate monthly S&OP meetings and monthly demand review meeting to align demand plans with Sales/Marketing, providing ROI simulations for new launches.
- Analyze supplier OTD performance and logistics variability to improve order fulfillment rate to 90%.

4. Data Governance & System Integration
- Maintain master data integrity across systems (ERP/BI), resolve data misalignment issues.
- Implement tools (e.g., Python-based models) in SAP IBP/APO or other system to automate planning workflows.

5. Supplier & Project Leadership
- Conduct quarterly supplier reviews to evaluate delivery performance (Target: 90%) and manage supplier return processes.
- Lead cross-functional projects (e.g., mega promotions), track capital requests and post-project KPI validation.

Qualifications
- Education: Bachelor’s degree or above in Supply Chain, Data Science, or related fields.
- Experience: 10+ years in planning (at least 5 year in demand planning); 3+ years team management; FMCG/Beauty industry experience would be preferred.
- Technical Skills:
- Data Mastery: Advanced Excel (Power Query/Pivot), SQL/Python for ETL; Power BI/Tableau dashboard design.
- Systems: Expert in SAP or other ; hands-on experience in ML-driven forecasting projects is a plus.
- Supply Chain Analytics: Proficient in safety stock modeling, Monte Carlo simulation, bottleneck analysis.
- Soft Skills:
- Ability to simplify technical insights for non-technical stakeholders (e.g., explaining ML logic to Marketing).
- Resilience under peak season pressure, flexibility for overtime.
- Language: Fluent English.