Wholesale Customer Service Associate

Los Angeles, California
01 Aug 2022
01 Sep 2022
Contract Type
Full Time

AMIRI is looking for a Wholesale Customer Service Associate to join our growing Los Angeles team!  This role requires someone who is outgoing, detail-oriented, and loves problem solving.  Our ideal candidate is tech savvy, energetic, and loves to "work smart."

What You'll Do:

  • Provide outstanding customer-facing support and interactions.
  • Respond to customer inquiries with consistency and quality in adherence to the Company's service level agreements.
  • Develop and own a strong product knowledge to guide the customer/accounts in recommendations.
  • Interpret customer intentions to proactively solve problems and recommend solutions from all current product offerings.
  • Process administrative items, respond to phone inquiries, stock checks, and other general inquiries.
  • Anticipate, answer, and address customers’ needs and provide support when needed.
  • Work to resolve customer service issues in a timely and thorough manner.
  • Assist with improving the Customer Service experience by increasing accuracy and efficiencies for the customer.

What You'll Bring:

  • High school diploma/GED required.
  • Computer literacy with Microsoft Office software programs – Excel skills are a must.
  • Minimum of 1-2 years of customer service work experience.
  • Strong communicator (written/verbal).
  • Ability to work collaboratively with employees at all levels in all departments.
  • Interest in being an acute problem-solver with critical thinking skills.
  • Maintain organization and attention to detail while multitasking in a challenging, fast-paced environment.
  • Ability to learn and retain extensive knowledge of products and/or services.
  • Efficiently learn and use complex software to find data in response to customer support inquiries.
  • Excellent people skills: must be empathetic, patient, confident, good-humored, and able to interact well with a broad spectrum of personality types.
  • Brand familiarity preferred.

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