Associate Merchandise Strategy & Analytics Planner

BoxLunch HQ - City of Industry, CA - Full-time

Description

Do you have organization skills so strong that your name might as well be Hermione? We’re looking for a Associate Merchandise Strategy & Analytics Planner to join the licensed product team and grow with us! In this role you’ll plan and analyze assigned merchandise categories.  You’ll also communicate hit, misses and go-forward strategies.  

Pay range

    $70,000 - $75,000 a year

    Please note the pay range for this position starts as listed in the job posting, but other factors such as an individual’s education, location, meeting the minimum job requirements for the role, training and experience, will determine the final salary for potential new hires.

WHAT YOU'LL DO

  • Analyze all aspects of the business including margin, sales, promotions, inventory, markdowns and product specific opportunities
  • Understand and optimize sales opportunities by channel
  • Communicate hits, misses, and go-forward strategies to the cross-functional team
  • Collaborate with buying team to determine business opportunities & with e-comm team to develop web sales strategies
  • Develops pre-season top-down/bottom-up level plans for sales, inventory, markdowns and margin in partnership with the Planning Manager and buyer
  • Initiates analysis of business trends, including but not limited to, category performance, web analytics, regional, selling, and size selling
  • Manages the Open to Buy with the Manager and the Buyer
  • Recommends test strategies based on current category performance and initiates analysis

WHAT YOU'LL NEED

  • An entrepreneurial spirit & the ability to drive the decision making process
  • 1 year of retail Allocation and/or Merchandise Planning experience
  • Associate/Bachelor’s degree or equivalent work experience.
  • Experience or conceptual understanding of the Arthur Allocation System
  • Strong analytical and quantitative skills
  • A positive outlook & an ability to go with the flow and adapt with change


Apply