Life Sciences Manufacturing Transformation Lead - AI & Data

EY

San Francisco (CA)

Remote

USD 188,000 - 391,000

Full time

4 days ago

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Job summary

EY is seeking a Senior Manager in Supply Chain Manufacturing to lead transformations for pharmaceutical, biotechnology, and medical-device clients, connecting plant operations with enterprise systems and data.

This techno-functional role requires credibility to redesign processes and operating models, directing teams delivering MES/MOM, automation, data and AI solutions, while owning delivery quality, risk, and client outcomes in regulated environments.

Qualifications

A bachelor’s degree in engineering, life sciences, manufacturing, supply chain, information systems, business, or related discipline.
No less than 10+ years of relevant Life Sciences manufacturing, manufacturing technology, operational excellence, industrial data and AI, technology consulting, or a related field.
Experience leading complex manufacturing transformation or technology-enabled improvement initiatives in a pharmaceutical, biotechnology, medical-device, or comparably regulated environment.
Experience delivering client-facing programs through design, implementation, deployment, and stabilization, with accountability for governance, resources, quality, financial performance, and risk.
Experience leading senior stakeholders and multidisciplinary teams across business, functional, data, and technology workstreams.
Experience translating manufacturing requirements into process, system, data, integration, security, and technical requirements, with traceability through testing and deployment.
Practical understanding of GxP manufacturing and the quality, documentation, change-control, and data-integrity considerations relevant to digital solutions.
Ability to travel as needed based on business and role requirements. Travel can range from 80-100%.

Responsibilities

Lead end-to-end Life Sciences manufacturing transformations, from assessment and mobilization through design, deployment, stabilization, and value realization.
Build trusted relationships with senior manufacturing, quality, MS&T, engineering, supply chain, digital, and IT/OT stakeholders; establish governance and drive timely decisions.
Translate priorities such as yield, throughput, right-first-time execution, deviation reduction, batch-cycle time, asset reliability, and supply continuity into practical workplans and outcome measures.
Direct multidisciplinary teams across manufacturing process design, MES/MOM, automation, data engineering, AI, architecture, integration, quality, change management, testing, and deployment.
Lead solution and process design for batch and discrete execution, electronic batch records, electronic device history records (eDHRs), recipes and routings, material and product genealogy, review by exception, maintenance, quality workflows, and plant performance management.
Guide integration across MES/MOM, ERP, LIMS, QMS, historians, SCADA, DCS/PLC, asset-management systems, and relevant cloud or edge platforms.
Establish trusted manufacturing data foundations through appropriate data models, asset and process context, master data, metadata, lineage, governance, and secure IT/OT connectivity.
Shape analytics and AI use cases, such as process monitoring, predictive maintenance, deviation investigation support, digital twins, and decision support; assess their value, data readiness, workflow fit, and risks before scaling.
Partner with client quality and validation teams to incorporate applicable GxP controls, data integrity, electronic-record requirements, change control, and risk-based assurance into delivery plans. The applicable controls will depend on the product, system, and intended use.
Manage scope, schedule, budget, staffing, dependencies, quality, risks, issues, and contractual commitments; guide testing, cutover, training, adoption, and operational handover.
Connect digital solutions to daily management, operational excellence, workforce capability building, and sustained process improvement.
Ability to create clarity and alignment across distributed teams, motivate people through complex delivery challenges, and maintain accountability without becoming the bottleneck for decisions.
People leadership and talent-development capability, including coaching, delegation, performance feedback, conflict resolution, succession planning, and building teams with the right mix of functional, technical, and industry skills.
Develop Managers and delivery teams, contribute reusable methods and lessons learned, and identify appropriate follow-on opportunities with account teams.