[Hiring] Director, CX Data and Customer Analytics @HealthEquity

Role Description

The Director, CX Data & Customer Analytics is the analytics leader for the Customer Organization, responsible for helping CX leadership understand, explore, define, and deliver scalable analytics and enterprise reporting that enables effective performance management, business growth, operational excellence, and continuous improvement in customer experience.

• Serve as the primary analytics and insights partner to CX leadership, helping leaders define strategic questions, customer experience measures, operating metrics, and decision needs.
• Build a deep understanding of HealthEquity's business model and how client, member, broker, and partner experiences connect to business performance, retention, growth, and operational efficiency.
• Quantify the value at stake—including retention, revenue, cost to serve, operational risk, and customer experience impact—and use it to build business cases, guide investment decisions, and prioritize the CX analytics roadmap.
• Translate business priorities into measurable outcomes, analytics strategies, reporting products, and action plans that drive customer and business results.
• Own the CX analytics roadmap, aligning investments to customer priorities, value at stake, strategic business objectives, executive priorities, operational reporting needs, regulatory and risk considerations, automation opportunities, and measurable business value.
• Develop scalable analytics, dashboards, scorecards, and enterprise reporting that help the Customer Organization monitor performance, identify risk, evaluate trends, and improve customer experience.
• Serve as a trusted advisor to CX leadership by translating complex analytics into clear business narratives, recommendations, and decision support for executive audiences.
• Establish intake, prioritization, and delivery practices that focus the team on the highest-value work while communicating tradeoffs in a supportive, transparent, and business-oriented manner.
• Negotiate competing priorities with stakeholders based on business value, urgency, reuse potential, risk, effort, and strategic alignment.
• Distinguish between ad hoc analysis, repeatable operational reporting, certified analytics, and scalable data products.
• Partner with Data Engineering and Technology teams to design, sponsor, and mature semantic models that enable governed, consistent, and performant analytics and reporting at scale.
• Partner with Data Governance to improve metric definitions, data quality, lineage, stewardship, certification, and trust in CX reporting and customer experience analytics.
• Use CX platforms, survey data, call center metrics, agent performance data, CSAT, NPS, customer journey signals, contact drivers, quality measures, and operational data to identify trends, root causes, opportunities, and risks.
• Apply data science fluency to increase pattern recognition, segmentation, driver analysis, predictive modeling, forecasting, anomaly detection, and proactive performance management across the Customer Organization.
• Partner with Data Science and AI teams to identify, prioritize, and operationalize advanced analytics and AI-enabled use cases.
• Drive report rationalization, automation, dashboard performance improvement, self-service enablement, and retirement of low-value or duplicative reporting assets.
• Measure analytics effectiveness through business outcomes influenced, decisions changed, stakeholder adoption, reporting quality, reduced manual effort, improved decision speed, customer experience improvements, and measurable business impact.
• Build, lead, and develop a high-performing analytics and reporting team that combines business partnership, technical depth, curiosity, accountability, and measurable impact.
• Create role clarity, delivery standards, operating rhythms, and development plans that improve team execution, stakeholder trust, and analytics maturity.
• Manage and carry out personnel actions for direct reports, including hiring, scheduling, coaching, training, performance management, compensation recommendations, and corrective or disciplinary action as appropriate.
• Provide hands-on guidance to analysts on SQL, Python, Databricks notebooks, dashboard logic, business rules, data validation, query performance, and reusable analytical patterns.

Qualifications

• Deep business acumen with a strong understanding of how customer experience influences retention, growth, customer lifetime value, operational efficiency, and cost to serve.
• Must be able to write SQL, Python, and Databricks notebooks/workbooks well enough to guide analysts, review logic, validate results, and advise on performance optimization.
• Deep understanding of analytics engineering concepts, semantic model design, dimensional modeling, metric definition, dashboard design, and scalable reporting patterns.
• Strong familiarity with customer experience and operational performance measures, including call center metrics, queue performance, handle time, first-contact resolution, abandonment, transfer rates, quality measures, CSAT, NPS, and customer experience trends.
• Experience with CX survey or Voice of Customer platforms such as Qualtrics or similar tools, and the ability to integrate survey signals with operational and behavioral data.
• Working knowledge of Databricks, lakehouse architecture, gold-layer data assets, BI platforms, governed metrics, and reusable data products.
• Data science understanding or hands-on experience in predictive modeling, classification, forecasting, segmentation, recommendation, anomaly detection, and pattern recognition.
• Understanding of agentic AI, AI assistants, and AI-enabled analytics patterns.
• Ability to partner with engineering teams on data model requirements, performance considerations, reusable logic, testing, data quality, reliability, and production readiness.
• Demonstrated ability to influence senior leaders and stakeholders without direct authority.

Requirements

• Bachelor's degree in Business, Economics, Analytics, Data Science, Computer Science, Information Systems, Statistics, Mathematics, Finance, Operations, or related field required; Master's degree preferred.
• 10+ years of progressive experience in customer analytics, CX analytics, business intelligence, customer insights, data science, consulting, strategy, or related disciplines.
• 5+ years of leadership experience managing analytics, BI, insights, reporting, or analytics engineering teams.
• Experience leading analytics transformation, reporting modernization, KPI standardization, self-service analytics, dashboard rationalization, customer intelligence programs, or semantic model adoption.
• Experience supporting senior leaders through operating reviews, performance management routines, executive dashboards, strategic planning, and decision support.
• Experience in healthcare, financial services, benefits administration, contact center operations, regulated environments, or consumer-facing service organizations preferred.
• Experience in consulting, customer intelligence, customer experience strategy, business intelligence, or customer insights environments preferred.
• Strong communication skills with the ability to make complex data actionable and explain technical tradeoffs to non-technical leaders.
• Strong people leadership skills with the ability to coach analysts, raise quality standards, develop talent, and create a culture of accountability and continuous improvement.

Benefits

• Medical, dental, and vision
• HSA contribution and match
• Dependent care FSA match
• Uncapped paid time off
• Paid parental leave
• 401(k) match
• Personal and healthcare financial literacy programs
• Ongoing education & tuition assistance
• Gym and fitness reimbursement
• Wellness program incentives