Remote Revenue & CRM Operations Specialist

YO AI Labs

New York (NY)

À distance

USD 83 000 - 124 000

Plein temps

14 jours+

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Résumé du poste

YO AI Labs is seeking an experienced Sales, Revenue, or Customer Success Operations expert to improve CRM-driven workflows, data accuracy, and reporting across SaaS environments.

You will configure CRM platforms (Salesforce, HubSpot), manage revenue tools such as quoting, billing, and ticketing, and build scalable processes to support revenue teams while maintaining data integrity and clear performance metrics.

Qualifications

  • 4+ years in Sales, Revenue, or Customer Success Operations.
  • Hands-on CRM configuration and management experience.
  • Experience with at least two revenue-related tools outside the CRM.
  • Strong operational judgment and problem-solving skills.
  • Excellent written and verbal communication.
  • Strong understanding of data accuracy, reporting, and workflow management.

Responsabilités

  • Configure and manage CRM platforms such as Salesforce, HubSpot, or similar tools.
  • Manage revenue tools including quoting, billing, ticketing, and project management systems.
  • Build and optimize sales and customer success workflows.
  • Maintain accurate data and reporting across connected systems.
  • Identify and resolve operational or policy-related challenges.
  • Create clear documentation, reports, and process guidelines.
  • Support system adoption and operational improvements.

Connaissances

CRM analytics
Process optimization
Data reporting
Documentation

Outils

Salesforce
HubSpot
Quoting tools
Billing systems
Ticketing systems
Project management tools

Description du poste

YO AI Labs is seeking an experienced Sales, Revenue, or Customer Success Operations expert to improve CRM-driven workflows, data accuracy, and reporting across SaaS environments.

You will configure CRM platforms (Salesforce, HubSpot), manage revenue tools such as quoting, billing, and ticketing, and build scalable processes to support revenue teams while maintaining data integrity and clear performance metrics.

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