Contact Center Expert - Business Analytics

Contact Center Expert - Business Analytics Say hello to opportunities. If you’re looking to be part of what’s next in communication, you’re in the right place. At RingCentral, we believe the best customer experiences happen when humans and AI work together. Our agentic voice AI portfolio—AIR, AVA, and ACE—brings together automation, assistance, and insights across the entire conversation lifecycle. The result? More seamless, intelligent experiences for businesses everywhere. With $2.5B+ in ARR and $250M invested in R&D annually, we’re building the future of AI-powered business communications. This is where you and your skills come in. We’re currently looking for:  The Contact Center Expert - Business Analytics role is a hands-on technical expert, not a general consultant or relationship manager. You will be building, configuring, and troubleshooting production environments. We value the insight gained from overcoming technical challenges and mistakes, as this experience directly benefits the customers you support. As a Contact Center Expert- Business Intelligence, you will provide deep domain expertise when a Technical Success Manager (TSM) identifies a complex customer need. Engagements range from targeted consultations and health checks to AI workflow design and optimization programs. These projects have specific scopes, costs, and timelines. While the TSM manages the overall customer relationship, you will lead the technical engagement from start to finish. Job Responsibilities: Customer Engagements Pull-in specialist: Engage as a pull-in specialist when the TSM identifies a customer need requiring domain depth - dashboards and reports, data and insights that drive actionable decisions, etc Time-bound engagements: Lead focused, time-bound customer engagements: discovery sessions, configuration reviews, dashboard and reporting reviews, and written findings with actionable recommendations AI QM scoring: Understands how AI QM scoring differs from human QM scoring - where AI adds accuracy and scale, where it introduces bias risk, and how to calibrate AI-scored evaluations against human benchmarks Customer education: Can explain to a customer why their AI-assisted QM scores may not match their human evaluation scores and what to do about it Professional delivery: Deliver findings and recommendations professionally - written output and verbal presentation to technical leads and senior business stakeholders ACE configuration : ACE configuration and optimization: mapping evaluation criteria to AI categories, calibrating auto-scoring thresholds, and designing AI QM reporting that gives supervisors actionable data RingSense assessment : RingSense deployment assessment: reviewing how a customer has configured post-call AI analytics - category setup, moment identification, trend analysis, and integration with operational workflows Agent/Supervisor AI : Agent assist and supervisor AI tools:…