Location: Al-Obour First Industrial Zone
Working Conditions: Sunday to Thursday
Working Hours: 08:00 AM to 04:30 PM
Key Responsibilities
1. Sales Forecasting & Historical Analysis:
- Develop and execute monthly and annual sales forecasts by analyzing historical data, market trends, and seasonal patterns across all product lines.
- Use statistical modeling and data-driven insights to predict future sales volumes for existing and new products.
- Perform regular audits and cleansing of sales data to ensure the foundation of the forecast is accurate.
2. Forecast Modeling & Development:
- Build and maintain advanced statistical forecast models (e.g., time series, regression) to support high-level business planning.
- Adjust baseline sales forecasts based on specific promotional calendars, marketing events, and market intelligence.
- Prepare detailed demand estimates for New Product Introductions (NPI) to ensure optimal stock levels from day one.
3. Accuracy Monitoring & Variance Analysis:
- Measure and track Sales Forecast Accuracy (e.g., MAPE, WAPE, Bias) and identify the root causes of any forecast errors.
- Analyze the “gap” between actual sales and forecasted figures, providing actionable insights to management to minimize future deviations.
4.Cross-Functional Demand Alignment:
- Lead monthly meetings with Sales and Marketing teams to gather field intelligence and incorporate it into the Sales Forecast.
- Communicate the final demand plan to the Supply Chain and Production departments to ensure alignment with operational capacity.
Qualifications & Skills
- Education: Bachelor’s degree in Business Administration, Finance, Statistics, Supply Chain, or a related field.
- Experience: 3–5 years of experience in demand planning or a similar analytical role.
- Mandatory experience in the Cosmetics industry or FMCG.
- Proven track record of managing multiple product lines (diverse SKUs) simultaneously.
- Technical Skills:
- Expert-level proficiency in Microsoft Excel (Advanced formulas, Pivot tables, Macros).
- Familiarity with Power BI or other data visualization tools.
- Competencies: * Strong quantitative skills with the ability to interpret complex data from various sources.
- Excellent communication skills for presenting complex data to stakeholders.
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