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Quality Optimization Analyst
Job in
Atlanta, Fulton County, Georgia, 30339, USA
Listed on 2026-03-07
Listing for:
GetInsured
Full Time
position Listed on 2026-03-07
Job specializations:
-
IT/Tech
Data Analyst, Data Science Manager
Job Description & How to Apply Below
In addition to eligibility determination, plan selection, and enrollment technology for state agencies, the company delivers innovative agent marketing and call center tools and services.
We are seeking a Quality Optimization Analyst who will be responsible for data, reporting, and analytics that support Quality Assurance and contact center performance. This role transforms quality and operational data into actionable insights that inform decision-making, improve customer experience, and strengthen quality outcomes across multiple interaction channels.
Partnering closely with Quality, Operations, Training, and Leadership teams, the Quality Optimization Analyst develops and analyzes reports, identifies trends and emerging risks, and translates complex data into clear, meaningful insights. This role plays a critical part in driving continuous improvement by ensuring leadership has accurate, timely, and relevant data to support performance optimization and strategic planning.
Key Responsibilities:
* Develop, maintain, and deliver quality and contact center performance reports, dashboards, and analytics across multiple interaction channels
* Analyze QA, operational, and customer experience data to identify trends, patterns, risks, and opportunities for improvement
* Ensure data accuracy, integrity, and consistency across reporting sources and quality metrics
* Translate complex datasets into clear, actionable insights for Quality, Operations, Training, and Leadership teams
* Support leadership reporting needs, including trend summaries, performance reviews, and executive-level insights
* Partner with Quality Assurance and cross-functional teams to define, refine, and align quality metrics and success measures
* Monitor the effectiveness of quality initiatives and process changes through ongoing data analysis
* Identify data gaps, reporting limitations, and opportunities to improve analytics capabilities
* Maintain documentation and reporting artifacts that are audit-ready and decision-ready
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