Quality Analyst - Primary Cybersource

Visa Visa · Fintech · Bogota, Colombia, CO

The Quality Analyst role at Visa focuses on advancing quality, risk, and control monitoring by using a combination of manual evaluation, AI-enabled quality intelligence, and data-driven insights. The role supports risk governance by performing quality reviews, monitoring controls, identifying risks, and enabling continuous improvement in customer interactions and operational processes. It involves analyzing patterns, identifying root causes, and influencing operational changes by partnering with various stakeholders. The role leverages AI-assisted tools and advanced analytics to generate insights, support governance of AI quality models, and deliver actionable narratives to leadership.

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. Identify quality defects, compliance risks, behavioral gaps, and control failures through manual and AI‑enabled analysis.
  4. Analyze quality, risk, and control data across segments, channels, and time to identify trends, systemic issues, and emerging risk themes.
  5. 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.

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.
  • 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
  • governance of Hu & AI driven quality models
  • AI-assisted quality monitoring
  • AI-driven quality signals

Other signals

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