The Quality Analyst – Speech Analytics & AI plays a critical role in monitoring and enhancing
the quality of customer interactions across multiple channels (calls, emails, chats). This role
involves leveraging speech analytics, AI-powered quality monitoring tools, and automation
to identify trends, improve agent performance, and enhance customer experience. The QA will
provide data-driven insights, coaching, and process improvement recommendations to optimize
customer service operations.

Key Responsibilities:
Speech Analytics & AI-Driven Quality Monitoring:
● Work closely with the AI development team to develop AI solutions and conduct
machine learning and accuracy testing
● Utilize speech analytics software to analyze call transcripts, detect sentiment, and
identify compliance risks or service gaps
● Apply AI-driven quality monitoring solutions to automate and enhance the evaluation
process, ensuring more comprehensive coverage of customer interactions
● Identify recurring themes in customer inquiries, complaints, and agent performance to
drive targeted training and operational improvements
● Support the AI development team to track customer sentiment, compliance
adherence, and escalation triggers
Call Monitoring, Evaluation & Compliance:
● Manually and systematically review customer interactions (calls, emails, chats) for
adherence to quality, compliance, and performance standards
● Use AI-driven analytics to identify coaching opportunities, sentiment trends, and
agent knowledge gaps
● Ensure compliance with industry regulations, data security standards, and
customer experience best practices

Coaching & Agent Development:
● Leverage AI-generated insights to provide targeted coaching and feedback to improve
agent performance
● Conduct data-backed coaching sessions, using real-time AI analytics to highlight
areas for improvement
● Collaborate with training teams to design AI-driven training modules based on
identified agent skill gaps
Process Improvement & Data Analysis:
● Identify emerging trends in customer interactions and provide recommendations to
improve service delivery
● Use speech analytics dashboards and AI-generated reports to present actionable
insights to leadership
● Work closely with IT and data science teams to optimize AI-based quality monitoring
tools
Reporting & Performance Metrics:
● Prepare detailed AI-driven quality reports highlighting agent performance, customer
sentiment trends, and compliance adherence
● Track KPIs such as Call Quality Scores, Customer Satisfaction (CSAT), Net
Promoter Score (NPS), and First Call Resolution (FCR)
● Monitor AI-generated predictive analytics to anticipate potential quality risks and
proactively implement solutions