CNG Holdings
Speech Analytics Administrator
Ohio - Remote
Sponsorship not specifiedDetected 16 days ago
Process ImprovementCustomer SupportMicrosoft Office
About the role
- The Speech Analytics Administrator role supports the administration and configuration of the organization's Conversation Intelligence platform (Cresta). This role is responsible for maintaining system configurations, assisting with enhancements, and ensuring the platform effectively supports business operations, compliance requirements, and performance
- monitoring. Responsibilities include managing system components (users, metadata, and analytics structures), supporting reporting capabilities, and assisting stakeholders in leveraging the platform for insights and operational improvements.
Requirements
- Bachelor's degree in business, technology, or related field or equivalent experience
- Experience with platform configuration, taxonomy design, or system administration
- Familiarity with call center technologies and speech analytics platforms
- Ability to communicate technical concepts to non-technical stakeholders
Nice to have
- 2+ years of experience administering or configuring speech/conversation analytics platforms (Cresta strongly preferred)
- 3-5 years of experience in Contact Center, QA, Compliance, or Operations within a regulated environment (financial services preferred)
Skills
- Assist in monitoring data quality and system performance, including validating outputs and identifying inconsistencies.
- Translate defined business and compliance requirements into system configurations and reporting logic.
- Contribute to governance efforts, including maintaining taxonomy structures, naming conventions, and documentation standards.
- Assist in prioritizing and completing platform requests and enhancements under direction.
- Contribute to process improvement initiatives by supporting platform enhancements and identifying opportunities for increased efficiency.
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This listing is sourced directly from CNG Holdings's careers page and normalized into a canonical job model.