Life Sciences Quality Transformation Lead

EY; Austin (TX); Remote; USD 128,000 - 257,000; Full time

Job summary

EY is seeking a Client-facing Life Sciences Manufacturing Quality Manager who leads technology-enabled transformation workstreams that strengthen quality systems, compliance, audit readiness, and product quality across manufacturing and laboratory operations.

The role blends practical quality-domain expertise with digital QMS, data, AI, and delivery skills to turn quality needs into scalable, regulated solutions. Travel up to 80–100% may be required.

Qualifications

• A 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

Quality domain knowledge

Data analytics

AI in quality

Stakeholder management

Workshop facilitation

Education

Bachelor’s degree in life sciences, engineering, quality, supply chain, information systems, business, or related discipline

Tools

LIMS

ERP

eQMS

QMS

Job description

EY is seeking a Client-facing Life Sciences Manufacturing Quality Manager who leads technology-enabled transformation workstreams that strengthen quality systems, compliance, audit readiness, and product quality across manufacturing and laboratory operations.

The role blends practical quality-domain expertise with digital QMS, data, AI, and delivery skills to turn quality needs into scalable, regulated solutions. Travel up to 80–100% may be required.