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Sr. Category Analyst (Wholesale)

Job Description - Sr. Category Analyst (Wholesale)

Description

This position is a #Hybrid role, requiring 3 days in the office per week. 

You will perform a valuable role in support of the sales team and build a strong partnership with our clients. 

You will conduct high-quality analysis and synthesis of multi-source data to evaluate item performance, assortment planning, and store clustering through the modular process, while leveraging effective communication & influencing to orchestrate action.  



Responsibilities
  • Provide analytical analysis, insights, and recommendations for category management projects and initiatives utilizing retailer POS and NielsenIQ/Circana (IRI) data sources and reporting tools.
  • System tools required: Retailer POS, Circana (IRI)/NielsenIQ
  • Strong analytics, insights, presentation, and storytelling skills
  • Participate in the development of category presentations incorporating syndicated data and other sources of data that address business issues
  • Work closely with CPG Category Management and Space Technology teams to ensure quality results are delivered
  • Keep abreast of client’s KPIs, strategies, innovation, and other important information.  
  • Leverage relationships with clients to understand key retailer deliverables, category strategies, and project timelines.
  • Category Analyst/Manager Certification is a plus. 


Qualifications

Education Requirements:

  • Bachelor's Degree
  • Related work experience may be substituted for the educational requirement

Work Experience Requirements:

  • 2+ years related experience

Knowledge, Skills, and Abilities Requirements:

  • Demonstrate an advanced degree of proficiency in Windows and related software applications, including Excel, PowerPoint, VB, and advanced macro’s.
  • Experience with syndicated data and/or space management tools.
  • Clearly and concisely communicate relevant information.
  • Identify and leverage relevant data to diagnose situations and identify potential solutions
  • Effectively and independently conduct data mining utilizing CPG math concepts and tools.  

 

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