Data-Driven Merchandise Allocator (Hybrid)

Super Retail Group; Sydney; Hybrid; AUD 70,000 - 90,000; Full time

Benefits offered by this job

Team discounts

Job summary

Super Retail Group is seeking a Product Allocator to optimise stock flow and maximise sales across assigned categories. You’ll own replenishment stock and core lines, ensuring products are where customers need them while keeping inventory lean.

You will collaborate with Merchandising Planners and Business Managers to execute stocking strategies, analyse demand patterns, and monitor performance across seasonal ranges.

Qualifications

• Experience in inventory forecasting, replenishment planning, allocation or merchandise planning.
• Ability to analyse sales data, demand patterns and inventory performance.
• Knowledge of stock turn, sell-through, weeks of cover and replenishment planning.
• Multitask across multiple categories with competing priorities.
• Experience with Netstock and Blue Yonder (JDA) is highly regarded.

Responsibilities

• Own inventory allocation across stores and distribution centres.
• Drive commercial performance to meet sales, gross profit and inventory targets.
• Collaborate with Merchandising Planners and Business Managers on stock strategies.
• Track aged and seasonal inventory and recommend improvements.
• Maintain accurate master data including season codes and refill metrics.
• Share insights with internal and external stakeholders to guide decisions.

Skills

Demand & Replenishment Planning

Forecasting & Analytics

Inventory Management

Multi-Tasking Pro

Netstock & Blue Yonder (JDA)

Tools

Netstock

Blue Yonder (JDA)

Job description

Super Retail Group is seeking a Product Allocator to optimise stock flow and maximise sales across assigned categories. You’ll own replenishment stock and core lines, ensuring products are where customers need them while keeping inventory lean.

You will collaborate with Merchandising Planners and Business Managers to execute stocking strategies, analyse demand patterns, and monitor performance across seasonal ranges.