Job Details

Job Description

Business Analyst (Retail/POS)

Overview:
We are seeking a Business Analyst to support replenishment planning and forecasting activities for a major retail partner. This role is part of a collaborative team focused on sales forecasting, inventory management, and order fulfillment. The analyst will work cross-functionally with internal teams and external partners to ensure optimal product availability and efficient supply chain execution.

Key Responsibilities:

• Drive in-stock performance by supporting end-to-end order processes, including order creation, daily order review, purchase order accuracy, and fill rate optimization.
• Support execution of direct import operations by coordinating with international customer service teams.
• Analyze sales trends and develop item-level forecasts to improve weekly point-of-sale (POS) projections.
• Collaborate with internal stakeholders and retail partners to align on forecasting and inventory plans.
• Develop and manage weekly shipping plans by item and channel to support demand and inventory targets.
• Participate in cross-functional planning meetings to present insights, share data findings, and contribute to consensus forecasting.
• Engage in collaborative forecasting discussions with external partners, providing recommendations and action plans based on business insights.

• Strong analytical skills with the ability to interpret data, identify trends, and recommend actionable solutions
• Effective communication and interpersonal skills, with the ability to collaborate across teams and organizational levels
• Sound business judgment and problem-solving capabilities
• Process-oriented mindset with a focus on continuous improvement
• Advanced proficiency in Microsoft Excel and MS Office tools
• Minimum of 2+ years of experience in sales analysis, inventory planning, or merchandising

• Experience in retail or consumer packaged goods (CPG) industries
• Familiarity with data visualization and analytics tools such as Power BI, Alteryx, or similar platforms
• Experience working with databases or large datasets (e.g., SQL-based tools)
• Knowledge of statistical forecasting methods and modeling techniques
• Experience in environments with seasonal demand and long lead times