Life Sciences Quality Transformation Manager

EY; Sacramento (CA); On-site; USD 128,000 - 235,000; Full time

Job summary

EY is seeking a Client-facing Life Sciences Manufacturing Quality Manager to lead technology-enabled transformation across quality systems, data, AI, and inspections in regulated environments. You will drive workstreams from assessment to implementation, with focus on data integrity and AI-enabled insights.

The role blends quality domain expertise with digital delivery, coordinating cross-functional teams and validating improvements in manufacturing, QA/QC, and laboratory operations.

Qualifications

• Bachelor’s degree in life sciences, engineering, quality, supply chain, information systems, business, or a related discipline.
• At least 7 years of relevant experience in Life Sciences Manufacturing Quality, QA/QC, quality technology, industrial data and AI, technology consulting, or a related field.
• Experience leading a client-facing quality, digital, data, or technology workstream through design and at least one implementation or deployment phase.
• Experience working in a pharmaceutical, biotechnology, medical-device, or comparably regulated manufacturing environment.
• Experience translating quality-domain needs into process, functional, data, integration, or testing deliverables and coordinating business and technical contributors.
• Practical understanding of GxP/GMP and the documentation, change-control, data-integrity, and electronic-records-and-signatures considerations relevant to digital quality solutions.
• Ability to travel as needed based on business and role requirements. Travel can range from 80-100%.
• Candidates must be legally authorized to work in the U.S. without the need for employer sponsorship, now and in the future

Responsibilities

• Lead client-facing workstreams in Life Sciences Manufacturing Quality transformation, with clear ownership of plans, deliverables, risks, decisions, and outcomes.
• Assess current-state quality processes, user needs, system landscapes, data flows, performance gaps, and site constraints through workshops, data analysis, and quality and laboratory engagement.
• Translate priorities such as right-first-time execution, cycle-time reduction, deviation and nonconformance reduction, CAPA effectiveness, and inspection readiness into process designs, requirements, acceptance criteria, and measurable improvements.
• Develop functional designs for relevant quality capabilities such as deviations/nonconformances and investigations, CAPA, change control, complaints, audits and inspection readiness, supplier quality, batch disposition/release and review by exception, and quality risk management.
• Coordinate integration requirements across eQMS/QMS, LIMS, MES/MOM, ERP, document-management, and laboratory-instrument and informatics systems, working with architecture, quality-systems, and cybersecurity specialists.
• Define and review data mappings, batch and investigation context, master-data needs, interface specifications, and data-quality controls needed for quality reporting, analytics, and AI use cases.
• Help deliver quality analytics and AI use cases, such as AI-assisted investigation and root-cause analysis, anomaly and trend detection, predictive quality, and quality decision support, by assessing data readiness, workflow fit, evaluation criteria, and human-in-the-loop review, governance, and controls.
• Work with client quality and validation teams to reflect applicable GxP/GMP, data-integrity, electronic-records-and-signatures, controlled-change, and validation or risk-based assurance requirements, including audit trails and traceability, in workstream deliverables.
• Oversee configuration activities and lead functional testing, defect resolution, deployment readiness, training, cutover support, hypercare, and handover for your workstream.
• Facilitate working sessions across quality, QA/QC, manufacturing, laboratory, MS&T, supply chain, IT, data, and technology-vendor teams; expedite decisions and dependencies that affect the broader program.
• Manage workstream scope, schedule, resources, quality, and risks; provide clear status updates and contribute to estimates, proposals, and follow-on opportunity shaping.
• Coach junior team members, review their work products, and capture reusable requirements, design patterns, and delivery lessons.

Skills

Client-facing leadership

Quality systems

Digital quality & AI

Education

Bachelor’s degree in life sciences, engineering, quality or related

Job description

EY is seeking a Client-facing Life Sciences Manufacturing Quality Manager to lead technology-enabled transformation across quality systems, data, AI, and inspections in regulated environments. You will drive workstreams from assessment to implementation, with focus on data integrity and AI-enabled insights.

The role blends quality domain expertise with digital delivery, coordinating cross-functional teams and validating improvements in manufacturing, QA/QC, and laboratory operations.