Senior Manager Business Intelligence, AI & Data Governance, CVRM

What You'll Do

• Design, deploy, and personally build site-wide BI dashboards, analytics pipelines, and KPI frameworks that support operational, quality, and executive decision-making
• Analyze plant data to proactively identify operational opportunities (yield optimization, cycle time reduction, energy efficiency, quality improvements) and partner with business functions to translate insights into action
• Co-design data visuals and analytics solutions with Operations, Quality, Engineering, and Warehouse teams, ensuring relevance and usability
• Establish and manage analytics time-to-insight standards, reducing lead time for operational reports and batch disposition analytics
• Lead the execution of AI/ML initiatives including predictive maintenance, yield optimization, and real-time operator decision support
• Drive measurable improvements in batch yield, equipment uptime (OEE), or downtime reduction through predictive AI models
• Ensure AI model validation and governance align with GxP requirements
• Establish and enforce site-wide data governance policies, data lineage protocols, and data quality assurance mechanisms for all non-ERP data sources (SCADA, MES, LIMS, historian systems, IoT platforms)
• Ensure compliance with FDA 21 CFR Part 11 and ALCOA+ principles across data operations
• Lead data quality assurance mechanisms and maintain 100% adherence to GxP/ALCOA+ standards
• Partner with Quality Assurance and Compliance teams to align data integrity protocols and AI validation strategies
• Establish data governance norms for the site, defining standards for data collection, storage, access, and usage
• Partner with IT/OT teams to design and oversee integration of data pipelines across SCADA, MES, LIMS, and ERP systems into a unified analytics data layer
• Collaborate on architectural decisions that ensure scalability, security, and regulatory compliance
• Monitor data integration completeness and drive continuous improvement in system connectivity
• Build, mentor, and lead a high-performing team of data engineers, BI developers, data scientists, and data governance specialists
• Foster a culture of technical excellence, continuous learning, and cross-functional collaboration
• Provide hands-on technical mentoring and code reviews; model best practices in design, analysis, and execution
• Develop team members' technical and leadership capabilities through coaching and growth opportunities
• Establish clear KPIs to quantify business value across BI, AI, and Digital Twin initiatives (e.g., reduction in batch cycle time, lower deviation rates, reduced energy consumption, improved OEE)
• Regularly report metrics and ROI to site leadership
• Proactively scout new manufacturing use cases, ROI opportunities, and continuous improvement projects to expand the Digital Twin's footprint and analytics capabilities

Who You Are

• B.S. or M.S. in Chemical Engineering, Mechanical Engineering, Data Science, Computer Science, Industrial Automation, or a related technical field
• 8+ years of experience in pharmaceutical manufacturing, process engineering, automation, data analytics, or industrial digital transformation
• Proven hands-on experience designing and building BI dashboards, analytics solutions, and data pipelines (SQL, Python/R, or equivalent)
• Hands-on experience with simulation, Digital Twin solutions, or advanced data modeling—demonstrating ability to drive insights and operational improvements
• Deep understanding of pharma plant operations (GMP, batch process control, PAT) paired with familiarity in data architectures (IoT, MES, SCADA, historian systems, simulation software like AspenTech, Ansys, or Siemens)
• Proven track record in managing product lifecycles, backlogs, and use case prioritization with demonstrated ability to translate complex business requirements into prioritized, actionable deliverables
• Strong background in building business cases and demonstrating value realization through data-driven metrics
• Experience establishing and enforcing data governance policies, data lineage, and quality assurance mechanisms in GxP-regulated environments
• Demonstrated expertise in FDA 21 CFR Part 11 and ALCOA+ compliance
• Experience leading data governance initiatives outside of ERP systems
• Demonstrated success in cross-functional stakeholder management, effectively bridging communication between technical teams, operations, engineering, and quality functions
• Ability to lead, mentor, and develop high-performing technical teams
• Experience driving organizational adoption of new technologies and methodologies

Certifications (Preferred)

• Agile/Scrum Product Owner (CSPO/PSPO)
• Lean Six Sigma (Green or Black Belt)
• Project Management Professional (PMP)
• GxP/ALCOA+ compliance certification or training