Senior Manager, eQMS Technologies
AbbVie
August 11, 2026
Remote friendly (North Chicago, IL)
United States
$124,500 - $236,500 USD yearly
Operations
Purpose
The Senior Manager – eQMS (electronic Quality Management System) Technologies enables data-driven quality and compliance decisions enterprise-wide through advanced analytics, AI-enabled insights, and measurement solutions.
Responsibilities
- Support development/execution of quality analytics and AI roadmaps aligned with RDQA, R&D, and Enterprise Quality priorities.
- Build/maintain automated reporting, dashboards, and KPI frameworks to monitor quality processes and eQMS health, performance, and compliance.
- Develop advanced analytics and AI capabilities (trend, anomaly, predictive risk signals) to identify quality/compliance risks earlier.
- Partner with process owners and BTS to translate business needs into analytics requirements, data products, and actions.
- Establish data definitions, quality controls, and governance for key quality datasets and metrics.
- Enable self-service dashboard/insight use via training, playbooks, and documentation.
- Review/approve SLC documentation for compliant use of data and models in regulated environments.
- Assess adoption/impact/performance; use feedback, statistical methods, root cause analysis, and data storytelling for continuous improvement.
Qualifications
Required:
- Bachelor’s degree (Pharmacy, Engineering, CS, Data/Analytics, Business, Chemistry, Biology, Microbiology, or related).
- 5–7 years in quality systems, engineering, data/analytics, or business support in a regulated environment.
- Experience creating metrics, dashboards, and analytical insights for process performance/compliance monitoring.
- Knowledge of data fundamentals (modeling, data quality, governance) and analytics methods (descriptive/inferential statistics, trend analysis).
Preferred:
- BI/analytics tools (e.g., Power BI) and SQL; Python/R scripting is a plus.
- ML/AI for operational quality (risk prediction, signal detection, text analytics) and model lifecycle (monitoring, bias, drift).
- Experience enhancing computerized QA/eQMS with data enablement/insights.
- Knowledge of decision-support tools/techniques and Risk Management principles.
- Quality Systems knowledge.
Travel: Yes, 10%.
The Senior Manager – eQMS (electronic Quality Management System) Technologies enables data-driven quality and compliance decisions enterprise-wide through advanced analytics, AI-enabled insights, and measurement solutions.
Responsibilities
- Support development/execution of quality analytics and AI roadmaps aligned with RDQA, R&D, and Enterprise Quality priorities.
- Build/maintain automated reporting, dashboards, and KPI frameworks to monitor quality processes and eQMS health, performance, and compliance.
- Develop advanced analytics and AI capabilities (trend, anomaly, predictive risk signals) to identify quality/compliance risks earlier.
- Partner with process owners and BTS to translate business needs into analytics requirements, data products, and actions.
- Establish data definitions, quality controls, and governance for key quality datasets and metrics.
- Enable self-service dashboard/insight use via training, playbooks, and documentation.
- Review/approve SLC documentation for compliant use of data and models in regulated environments.
- Assess adoption/impact/performance; use feedback, statistical methods, root cause analysis, and data storytelling for continuous improvement.
Qualifications
Required:
- Bachelor’s degree (Pharmacy, Engineering, CS, Data/Analytics, Business, Chemistry, Biology, Microbiology, or related).
- 5–7 years in quality systems, engineering, data/analytics, or business support in a regulated environment.
- Experience creating metrics, dashboards, and analytical insights for process performance/compliance monitoring.
- Knowledge of data fundamentals (modeling, data quality, governance) and analytics methods (descriptive/inferential statistics, trend analysis).
Preferred:
- BI/analytics tools (e.g., Power BI) and SQL; Python/R scripting is a plus.
- ML/AI for operational quality (risk prediction, signal detection, text analytics) and model lifecycle (monitoring, bias, drift).
- Experience enhancing computerized QA/eQMS with data enablement/insights.
- Knowledge of decision-support tools/techniques and Risk Management principles.
- Quality Systems knowledge.
Travel: Yes, 10%.