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Contact Center Expert - Business Analytics
Full-time
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: assessing configuration of real-time guidance triggers, escalation recommendations, and supervisor alert logic - and measuring whether the tools are improving agent performance
Transcript analytics: Transcript analytics health checks: evaluating the quality and consistency of AI-generated transcripts and the accuracy of the insights derived from them
AI QM calibration: AI QM calibration engagements: helping customers align their AI-scored evaluations with human-evaluated benchmarks - identifying systematic scoring gaps and recommending configuration changes
Conversation intelligence: Conversation intelligence strategy: advising customers on how to use AI-generated insights operationally - which metrics to act on, how to build coaching programs around AI data, and how to close the loop between insights and behavior change
Native reporting: Native reporting health checks: assessing how a customer has configured RingCX and RingEX reporting against their actual operational needs
Custom dashboards: Custom report and dashboard design: real-time agent dashboards, supervisor wallboards, queue performance views, and historical trend reports
Metric definition: Metric definition and alignment: ensuring RingCentral reporting produces accurate, consistent numbers for AHT, ASA, FCR, CSAT, occupancy, and utilization
WFM alignment: Reporting for WFM alignment: ensuring contact center reporting feeds align with the interval and metric requirements of the customer's WFM platform
BI integration: At the 12-month milestone: independently advise customers on RingCentral-to-BI platform integration - data export configuration, PowerBI/Tableau schema guidance, and API-based data pull patterns in collaboration with Lane 2
Product Feedback
Document gaps: Document recurring product gaps, configuration limitations, and customer-requested capabilities observed across engagements
SME feedback: Submit structured input through the SME-to-Product feedback channel after each engagement
Beta programs: Participate in product beta programs and early access initiatives within your specialty lane
Internal Knowledge
Product knowledge: Maintain current, deep knowledge of your specialty lane across all RingCentral products.
Knowledge resources: Contribute to all knowledge resources for RingCentral teams
Competitive platforms: Stay current on competitive platform capabilities (NICE CXone, Genesys, Five9, Zoom) within your domain
How You Work
Communication: Communication is top notch - you speak professionally, cordially, and personable
Ownership: Ownership - you own your communication as well as the tasks, don’t let balls drop, you follow up and follow through
Direct and specific: you communicate with precision about technical topics and don't hide behind vague language
Credible under pressure: you are comfortable being challenged by technically sophisticated customers or internal engineers
Efficient: you scope an engagement clearly, work within it, and produce output that is usable without extensive editing
Technical focus: You do not need to be a natural relationship-builder; the TSM handles that. You need to be professional, prepared, and technically unimpeachable
To succeed in this role you must have experience in:
Candidates must demonstrate specific, verifiable expertise in reporting, analytics, and insights, with personal accountability for design and delivery in enterprise environments. You must have personally deployed and tuned AI insights tools in a contact center environment—not just managed the vendors who did. While reporting tells you what happened, AI insights tell you what it means and what to do about it.
The following are illustrative examples of the kind of experiences we're looking for.
Building, configuring, and data accuracy: Minimum 5 years of
