Manager - Data, Analytics & Automation - Regulatory Affairs, Quality Assurance & Clinical

What You Will Do

• Lead and develop a team responsible for data analytics, reporting, automation, and governance across multiple business units and sites.
• Define and execute divisional strategies for data, analytics, reporting, automation, and value realization, including prioritization, resource planning, and budget alignment.
• Establish accountability for data ownership, reporting standards, dashboard management, automation intake processes, and ongoing support models.
• Standardize metric definitions, data sources, reporting practices, and data lineage documentation to improve reporting consistency and data integrity.
• Identify and scale reusable dashboards, reports, data models, and automation solutions that reduce duplicated effort across the division.
• Drive automation and advanced analytics initiatives that reduce manual work, improve cycle times, and support operational efficiency.
• Partner with business, technology, quality, regulatory, and clinical stakeholders to align priorities, governance practices, and platform strategies.
• Lead portfolio planning, capacity management, performance monitoring, and change management activities for analytics and automation programs.
• What You Will Need
• Required Qualifications
• Bachelor's degree in Data Analytics, Computer Science, Information Systems, Engineering, Quality, Regulatory Affairs, Statistics, Mathematics, Business, or a related discipline.
• Minimum 2 years of people leadership experience.
• Minimum 8 years of experience in data analytics, business intelligence, automation, quality systems, regulatory affairs, operations, or a related field.
• Minimum 2 years of experience leading enterprise-level data, analytics, reporting, automation, or quality system initiatives across multiple business units, functions, or locations.
• Experience implementing data governance, reporting, analytics, or automation capabilities within a complex business environment.
• Preferred Qualifications
• Advanced degree in Data Science, Analytics, Information Systems, Engineering, Business, or another quantitative discipline.