Client Care Quality Analyst

Visa Visa · Fintech · Pasay, Philippines, Philippines

This role focuses on quality assurance and risk monitoring within a customer service environment, leveraging AI-assisted tools to analyze customer interactions and identify areas for improvement. The primary output is improved quality and risk control in existing customer service operations, rather than the direct development or deployment of AI models themselves.

What you'd actually do

  1. Perform end‑to‑end quality reviews of customer interactions across voice, chat, email, case, and back‑office channels, ensuring accuracy, consistency, and compliance with documented standards.
  2. Support human‑in‑the‑loop AI quality monitoring, including reviewing assisted and automated scoring outputs and providing structured feedback to improve model performance.
  3. Analyze quality, risk, and control data across segments, channels, and time to identify trends, systemic issues, and emerging risk themes.
  4. Leverage AI tools (e.g., Copilot, assisted scoring, topic mining, speech and text analytics) to accelerate insight generation while validating AI outputs for accuracy and defensibility.
  5. Identify systematic gaps in Auto/AI scoring and support governance efforts to improve model signal fidelity and exception handling.

Skills

Required

  • Experience performing quality assurance, testing, risk, or control monitoring activities in a customer service or operations environment.
  • Demonstrated ability to conduct manual quality reviews and support AI-assisted quality monitoring under moderate supervision.
  • Strong analytical and critical-thinking skills with the ability to identify trends, root causes, and performance gaps.
  • Proficiency with Microsoft Office tools (Excel, PowerPoint, Word) and experience navigating multiple systems and data sources.
  • Ability to clearly document findings, communicate insights, and collaborate effectively with cross‑functional stakeholders.

Nice to have

  • Experience analyzing quality signals across both human‑delivered and AI‑delivered interactions.
  • Proficiency with data visualization and analytics tools (e.g., Power BI, Tableau) to build dashboards and performance reporting.
  • Experience translating automated quality outputs into prioritized coaching, remediation, or process improvement insights.
  • Familiarity with AI‑enabled quality tools, speech/text analytics, and assisted scoring methodologies.

What the JD emphasized

  • AI‑enabled quality intelligence
  • AI-assisted quality monitoring
  • AI-driven quality signals
  • governance of Hu & AI driven quality models