Principal Analyst Workforce & Service Performance

Job Description The principal analyst sets standards and leads advanced analytics and automation across Workforce Management (WFM) and Quality Assurance (QA) for multiple teams within the Zendesk organization. Solves unique, complex, and ambiguous problems with broad business impact, driving change through data, models, experiments, and frameworks. Operates with high autonomy, determining methods and procedures on new or special assignments and shaping WSP direction through recommendations, standards, and measurable outcomes. Key Responsibilities: Strategy Shaping & Standards Translate business goals and business targets into WFM/QA analytical roadmaps, standards, and reference models adopted across teams. Produce playbooks for forecasting, capacity, intraday, and backlog management; build QA scorecards/calibration guides; define metrics/data; and set governance rules. Establish experimentation standards (A/B, quasi-experimental, test/control), scenario modeling, and business casing to advise senior leaders on trade-offs and prioritization. Define guardrails for ethical/secure data use and model risk management (validation, monitoring, drift). Advanced Workforce Management Build trend-based forecasts for each channel over different timeframes and confirm reliability with scenario and risk simulations. Create capacity and hiring plans incorporating seasonality, marketing campaigns, sales projections, policy/product changes, and attrition; quantify impacts of AHT, shrinkage, adherence, and occupancy. Recommend scheduling strategies that balance SLA/ASA, cost, and agent experience; quantify impacts of AHT, shrinkage, adherence, and occupancy. Lead intraday/variance analysis and event/outage modeling; define corrective actions and run controlled experiments. Quality Management Analytics Design and maintain QA frameworks, sampling plans, calibration routines, and reliability checks to ensure fair, consistent measurement. Integrate speech/text analytics and VoC/CSAT/NPS to detect defects and behavior gaps; quantify impact and drive closed-loop action via coaching, enablement, or process/product changes. Validate automated QA/tag accuracy; monitor impact on customer satisfaction, first-contact resolution, repeat contacts, defects, and resolution time. Insight, Automation, & Tooling Build executive-ready dashboards and narratives linking operational drivers to business outcomes. Define data models and metric definitions for WFM/QA; ensure data quality and lineage. Lead adoption of automation and AI-assisted analytics to reduce manual effort and accelerate time-to-insight; partner with IT/Product/vendors on evaluation, configuration, integrations, and monitoring. Cross-functional Influence & Program Execution Create formal networks and facilitate recurring forums (forecast reviews, calibrations, performance deep dives) across Operations, Sales, Success, Enablement, Finance, and Product/IT. Lead complex cross-functional workstreams and pilots end to end (charter, plan, risks, measurement, change management); document decisions and trade-offs. Serve as a WFM/QA Center-of-Excellence voice, mentoring peers, conducting training, and uplifting analytic capabilities without direct people management. Risk, Compliance, & Change Management Ensure compliance and privacy in QA programs and data usage; anticipate risks and build mitigations. Anticipate risks (model drift, data quality, operational resiliency) and implement mitigations; maintain audit-ready documentation. Plan and execute change management for new processes and tools; measure adoption and effectiveness and iterate. Key Outcomes and Measures Forecast accuracy and staffing efficiency (AHT, Forecast accuracy, staffing efficiency, schedule efficiency index; healthy occupancy/adherence with agent wellbeing considerations. SLA/ASA/abandon attainment across channels with optimized cost per resolved contact and backlog health (for async channels). QA performa ... (truncated, view full listing at source)