Intern - Customer Success Manager

DomoAmerican Fork, UT

About The Position

Domo's AI and Data Products Platform lets people channel AI and data into innovative uses that deliver a measurable impact. Anyone can use Domo to prepare, analyze, visualize, automate, and build data products that are amplified by AI. Working as a member of Domo's Customer Success team, the Customer Success Intern will support scaled operations and AI-driven automation across 1,500+ customers. Equal parts technical execution and operational support, this role is ideal for a candidate pursuing a technical or business degree who wants to see how AI directly impacts a revenue-generating team. The intern will contribute to data workflows and agent builds that enable CSMs to spend more time delivering high-value customer experiences.

Requirements

  • Working towards a degree in Information Systems, AI/ML, Business Management, or work in a related technical field
  • Coursework or project experience in AI, machine learning or automation
  • Strong attention to detail – work directly impacts CSM capacity across hundreds of accounts
  • Ability to translate operational problems into technical solutions
  • Self-directed with the ability to manage multiple projects at once
  • Great verbal and written skills
  • Excellent communication, and presentation skills
  • Self-driven, motivated and results oriented.

Responsibilities

  • Support daily CSM operations by handling forecasting, Salesforce administrative tasks, asset identification, and routine data pulls across Domo, Gong, Salesforce, Salesloft, etc.
  • Build and maintain AI agents and automation solutions that improve scale, productivity, and consistency across the Customer Success organization
  • Develop and expand automation workflows that shift repetitive execution away from CSMs, returning productive capacity for renewals, expansion, and customer relationship management
  • Identify and implement process efficiency improvements that reduce administrative burden and increase customer-facing time for the broader CS team.
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