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AbbVie
Senior Manager, eQMS Technologies
Career Insights for Analytics Product Manager
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What they do
An Analytics Product Manager is responsible for managing a strategy to develop and/or sell analytical services or analytics products. May involve planning and assisting in the development, marketing and distribution of the product.
$162,566 / year median in Illinois
+4% projected growth
Job Description
Company DescriptionAbbVie's mission is to discover and deliver innovative medicines and solutions that solve serious health issues today and address the medical challenges of tomorrow. We strive to have a remarkable impact on people's lives across several key therapeutic areas•immunology, oncology, neuroscience, and eye care•and products and services in our Allergan Aesthetics portfolio. For more information about AbbVie, please visit us at www.abbvie.com. Follow @abbvie on X, Facebook, Instagram, YouTube, LinkedIn and Tik Tok.
Job DescriptionPurpose The Senior Manager• eQMS (electronic Quality Management System) Technologies is responsible for enabling data-driven quality and compliance decisions across the enterprise by developing and deploying advanced analytics, AI-enabled insights, and measurement solutions. This role partners with Quality, Business Technology Services (BTS), and process owners to define and execute the quality data strategy, improve data quality and accessibility, and deliver dashboards, metrics, and advanced analytics/AI that support continuous improvement, and global regulatory compliance. The position helps ensure effective quality insights and services are in place across R D to support more informed decision making, and proactive risk management in accordance with applicable policies, processes, procedures, and global regulatory requirements. Responsibilities Support the development and execution of quality analytics and AI roadmaps aligned with RDQA, R D, and Enterprise Quality priorities. Build and maintain automated reporting, dashboards, and KPI frameworks to monitor quality processes and eQMS health, performance, and compliance. Develop advanced analytics and AI capabilities (e.g., trend, anomaly, and predictive risk signals) to identify quality and compliance risks earlier. Partner with process owners and BTS to translate business needs into analytics requirements, data products, and insight-driven actions. Establish data definitions, quality controls, and governance for key quality datasets and metrics. Enable self-service use of dashboards and insights through training, playbooks, and documentation. Review and approve SLC documentation to support compliant use of data and models in regulated environments. Assess the adoption, impact, and performance of analytics solutions; apply feedback, statistical methods, root cause analysis, and data storytelling to drive continuous improvement.
Job DescriptionPurpose The Senior Manager• eQMS (electronic Quality Management System) Technologies is responsible for enabling data-driven quality and compliance decisions across the enterprise by developing and deploying advanced analytics, AI-enabled insights, and measurement solutions. This role partners with Quality, Business Technology Services (BTS), and process owners to define and execute the quality data strategy, improve data quality and accessibility, and deliver dashboards, metrics, and advanced analytics/AI that support continuous improvement, and global regulatory compliance. The position helps ensure effective quality insights and services are in place across R D to support more informed decision making, and proactive risk management in accordance with applicable policies, processes, procedures, and global regulatory requirements. Responsibilities Support the development and execution of quality analytics and AI roadmaps aligned with RDQA, R D, and Enterprise Quality priorities. Build and maintain automated reporting, dashboards, and KPI frameworks to monitor quality processes and eQMS health, performance, and compliance. Develop advanced analytics and AI capabilities (e.g., trend, anomaly, and predictive risk signals) to identify quality and compliance risks earlier. Partner with process owners and BTS to translate business needs into analytics requirements, data products, and insight-driven actions. Establish data definitions, quality controls, and governance for key quality datasets and metrics. Enable self-service use of dashboards and insights through training, playbooks, and documentation. Review and approve SLC documentation to support compliant use of data and models in regulated environments. Assess the adoption, impact, and performance of analytics solutions; apply feedback, statistical methods, root cause analysis, and data storytelling to drive continuous improvement.