Director of AI & Digital Analytics

Overview:

National Debt Relief is seeking a strategic and insights-driven Director of Digital & AI Analytics to design the measurement, insights and optimization of our end-to-end customer experience. This role will own the enterprise-wide analytics strategy related to digital journeys and AI interaction support within client journeys. With a key focus on ensuring that the data we collect is used to create a competitive advantage in driving growth, efficiency, and client satisfaction. This role will be a key partner in supporting testing, performance management, and scale of agent-replacement AI within the organization.

As a Director, you will lead a team and partner cross-departmentally to ensure that the data insights inform decision making and support the long term experience strategy for the company. Expectations are to be both a leader of team as well as direct contributor/partner in improving customer journeys, increases conversion rate, and enhances client satisfaction.

Responsibilities:

• Define and lead the digital and client experience analytics strategy, aligning with business priorities and objectives.
• Drive the vision for data collection and data governance across the digital platforms such as event tracking, tagging and KPIs.
• Lead and mentor a team of analysts, fostering professional growth and building best-in-class analytics.
• Partner with executives to translate data-driven insights into business strategy.
• Guide the development of advanced dashboards, scorecards, and reporting to ensure insights are delivered to the right stakeholders at the right time.
• Oversee the customer journey analytics to identify pain points, opportunities and improvements in digital experiences.
• Collaborate with data engineering to ensure data flows into Snowflake for unified analytics.
• Stay ahead of digital analytics trends, data privacy regulations (GDPR, CCPA), and evolving best practices in customer experience measurement.
• Own the analytics strategy for AI Analytics, building the measurement framework that governs agent-replacement AI interactions across voice and chat channels.
• Lead test design and results analysis for AI model and prompt experiments (e.g., model version A/B tests, containment vs. escalation testing) to validate performance before scaling.
• Define and monitor performance KPIs for AI-handled interactions — containment rate, accuracy, quality/CSAT, and escalation rate — and translate findings into optimization roadmaps.
• Partner with AI Analytics, Speech Analytics, and Engineering teams to ensure AI interaction data (transcripts, model outputs, outcomes) flows into unified dashboards for real-time visibility.
• Guide the scale-up of AI-handled interaction volume, balancing performance thresholds, risk, and client experience as agent-replacement AI expands across channels.

Qualifications:

Education/Experience:

• Bachelor’s degree in Data Analytics, Business Analytics, Statistics, Computer Science, Marketing, Business, or a related field; or equivalent combination of education and relevant experience.
• 10+ years of experience in digital, product, or marketing analytics, including 3–5 years in a leadership role.
• Proven track record of building and leading analytics teams.
• Demonstrated experience with customer experience (CX) optimization, funnel performance tracking, and self-service channel performance.
• Experience analyzing conversational AI/LLM-driven interactions, including chat or voice bots and associated containment, accuracy, and quality metrics.
• Experience designing and evaluating A/B tests for AI models or prompts and translating results into clear go/no-go recommendations.
• Experience in financial services or fintech, particularly client onboarding or customer support journeys, preferred.
• Track record of driving enterprise transformation through analytics strategy, preferred.

Required Skills/Abilities:

• Strong SQL skills, with Snowflake experience preferred, and proficiency in data modeling and manipulation.
• In-depth knowledge of digital analytics platforms such as GA4, Adobe Analytics, Mixpanel, or similar tools.
• Proficiency with tag management systems such as Google Tag Manager (GTM), Adobe Launch, or Tealium.
• Strong knowledge of A/B testing frameworks and experimentation design.
• Proficiency with data visualization and dashboarding tools such as Tableau, Sigma, Looker, or Power BI.
• Ability to communicate complex data and analytical findings …