Director, Quality Intelligence Programs

About The Team

The Quality Intelligence team is a dynamic group of program managers, insights managers, and development leaders who collaborate cross-functionally to drive measurable behavior change and positive customer outcomes. The team sits within the Customer Experience Operations organization, and partners closely with other shared service groups, including but not limited to Engineering, Data & Analytics, Operations Strategy, and Frontline Leadership.

Right now, the team is at a pivotal stage of evolution, responsible for transforming quality from a monitoring function into an intelligence engine that captures and interprets customer interactions, integrates with enterprise systems, and delivers real-time, actionable insights. This transformation requires rethinking governance, redefining how insights flow into coaching and product feedback loops, and embedding quality intelligence directly into frontline workflows.

Our mission is to build a trusted quality intelligence program that not only measures performance, but actively shapes how we learn, improve, and deliver value to customers at scale.

About The Role

The Director, Quality Intelligence Programs is responsible for building and operationalizing quality as a scalable, intelligence-driven capability that measurably improves frontline behavior, customer outcomes, and enterprise decision-making. This role leads the end-to-end program that governs how quality data is generated, integrated, interpreted, and activated across Customer Experience Operations (CXO).

This leader owns both the implementation and modernization of our AI-powered quality intelligence platform and the programmatic translation of quality insights into action: coaching, training, automation, and product feedback loops. They will move quality from a retrospective scoring function to a continuously evolving system that informs real-time interventions and long-term CX strategy. Operating at the intersection of technology, operations, and change management, this role ensures quality intelligence is embedded in workflows, enterprise data systems, and executive decision-making. Success requires strong program leadership, technical fluency, cross-functional influence, and a relentless focus on execution and adoption.

This individual will know they are successful with: 1) the successful integration of quality data into a customer intelligence ecosystem; 2) sustained improvement in automated insight accuracy; 3) demonstrated linkage between quality insights and measurable improvements in CSAT; and 4) executive confidence in quality monitoring as a core data asset supporting customer strategy.

Key Responsibilities

• Lead the Quality Intelligence function: Define and execute the long-term vision for quality monitoring as a data intelligence function, not a manual evaluation process.
• Establish governance framework for transcription, sentiment detection, and behavioral analytics.
• Ensure the platform continuously evolves in accuracy, coverage, and insight depth through feedback loops and data calibration.
• Govern Quality Data Infrastructure: Own the integrity and reliability of all quality-related data flowing into the central customer intelligence base, ensuring alignment with data standards.
• Partner with engineering and Analytics to integrate quality signals with CSAT and operational metrics.
• Ensure bi-directional data sharing between Quality platform, knowledge base, and CXO data that supports enablement, product feedback, and automation initiatives.
• Enable Actionable Insight & Intervention: Translate model outputs into insights that inform coaching, training, and product improvement.
• Build closed-loop systems where quality insights automatically generate intervention recommendations or learning pathways for frontline teams.
• Technical Ownership & Innovation: Oversee configuration and management of speech and text analytics, including taxonomy evolution and sentiment weighting.
• Lead efforts to benchmark AI model accuracy and drive improvement.
• Ensure alignment with broader enterprise data architecture, API frameworks, ML governance standards, and responsible AI practices.
• Executive Stakeholder Management: Serve as the strategic bridge between CXO, tech, and executive leadership.
• Communicate the value, performance, and impact of quality intelligence in clear business terms, and drive executive alignment and investment around data-driven quality as a cornerstone of CX strategy.
• Team Leadership & Capability Development: Build and lead a multidisciplinary team spanning platform administration, program management, and analytical enablement.
• Foster a culture of analytical curiosity, operational rigor, and ethical AI use.
• Establish KPIs and learning plans that continuously elevate internal technical capability.

Who you are

Technical Expertise:

• Strong working knowledge of speech and text analytics, NLP concepts, and AI model lifecycle governance.
• Proven ability to manage complex, cross-system programs involving CRM, CSAT, telephony, and workforce management systems.
• Familiarity with API orchestration, data pipeline design, and cloud data environments, and comfort partnering with engineering and data teams.
• Experience evaluating or configuring quality monitoring or conversational intelligence platforms.
• Strong grounding in data ethics, privacy frameworks, and responsible AI principles.

Leadership & Strategic Capabilities:

• 10+ years of experience in CX, Technology Enablement, Analytics, or Operations, including 5+ years in a senior leadership role.
• Demonstrated success leading data-centric transformation initiatives within large or complex organizations.
• Strong executive communication and storytelling skills; able to translate complex data narratives into clear strategic decisions.
• Ability to build influence across technical, operational, and executive domains.
• Masters degree in Data Science. Business Analytics, Operations or related fields preferred.

Key skills/competency

• Quality Intelligence
• Program Leadership
• Speech Analytics
• Text Analytics
• Natural Language Processing
• AI Model Governance
• Data Integration
• Customer Experience Operations
• Executive Stakeholder Management
• Change Management