Quality Specialist Jobs

About The Position

Requirements

• Associate or bachelor's degree, or equivalent experience.
• At least 2 years of call center experience, preferably in healthcare, pharmaceutical, patient assistance, or regulated environments.
• Strong analytical skills and high attention to detail.

Nice To Haves

• Experience supporting pharmaceutical manufacturer foundations or patient support programs.
• Experience with quality monitoring tools or advanced speech analytics platforms.
• Knowledge of eligibility processing, CRM systems, and data quality standards.
• Understanding of adverse event reporting concepts and compliance requirements.
• Familiarity with FDA pharmacovigilance concepts and adverse event workflows.
• Experience supporting audits or compliance validation efforts.
• Exposure to AI governance, model validation, or quality technology implementations.

Responsibilities

• Work with leadership to refine AI-driven quality models for evaluating call handling, documentation accuracy, and eligibility case processing.
• Validate AI-generated quality scores, insights, and flags against approved quality standards, SOPs, and regulatory requirements.
• Review selected calls and cases with human oversight to verify AI accuracy and identify model gaps or bias.
• Recommend adjustments to AI scoring logic, thresholds, and evaluation criteria based on validation findings.
• Validate AI reviews of inbound and outbound calls for accuracy, professionalism, compliance, and policy adherence.
• Partner with leadership on AI-driven audits of eligibility cases in the CRM system to confirm data integrity, completeness, and correct eligibility determinations.
• Identify trends and systemic issues surfaced by AI analytics and escalate findings to Quality and Operations leadership.
• Partner with leadership to establish standards for AI detection and classification of potential adverse event calls and documentation.
• Ensure AI workflows identify, capture, and route adverse events in accordance with pharmacovigilance and regulatory requirements.
• Partner with Safety and Compliance teams to address AI accuracy issues involving adverse event handling and reporting.
• Lead AI quality calibration sessions with Quality leadership, Operations, and Training teams.
• Maintain governance documentation for AI quality rules, scoring logic, and validation protocols.
• Support continuous improvement initiatives to maintain consistent AI quality across agents, programs, and call types.
• Respond to internal, client, and external data validation audits related to AI-generated quality results.
• Provide validation evidence, test results, and documentation supporting the accuracy and reliability of the AI quality system.
• Conduct periodic validation testing.
• Review and share AI-generated quality trends and performance dashboards with leadership.
• Partner with the Manager of Quality on compliance reporting.
• Partner with vendors or internal technical teams to improve AI quality performance as needed.