Supply Chain Operations - Life Sciences Manufacturing Quality - Senior

EY•Hartford, DC

17h•$97,300 - $202,600

About The Position

As a Senior in Supply Chain Manufacturing Quality, you will work with pharmaceutical, biotechnology, and medical-device clients to connect Quality Assurance, Quality Control, laboratory, manufacturing, engineering, and supply chain needs with deployable technology. You will contribute across the delivery lifecycle, from quality-process and system assessments through requirements, solution design, configuration support, testing, validation, deployment, adoption, and stabilization. You will work directly with Quality Assurance, Quality Control, laboratory, manufacturing, regulatory, IT, data, and technology-provider teams. You will own assigned technical and functional deliverables, help resolve implementation issues, and make clear recommendations to your workstream lead. The role combines practical knowledge of quality systems and QA/QC processes with hands-on skills in digital QMS, laboratory systems, data integration, analytics, and AI-enabled quality workflows. The position is listed for anywhere in the country. Travel may range from 80–100% as needed based on business and role requirements. Candidates must be legally authorized to work in the United States without employer sponsorship, now and in the future. EY accepts applications on an ongoing basis.

Requirements

Bachelor’s degree in life sciences, quality, engineering, information systems, computer science, supply chain, or a related discipline.
At least 3 years of relevant experience in Life Sciences quality, Quality Assurance, Quality Control, laboratory systems, digital QMS, systems implementation, technology consulting, or a related field.
Experience working with quality, laboratory, or manufacturing processes in a pharmaceutical, biotechnology, medical-device, or comparably regulated environment.
Experience with one or more core quality processes, such as deviations, investigations, CAPA, change control, complaints, audits, supplier quality, batch disposition, release, or quality risk management.
Experience producing technical or functional delivery artifacts, such as requirements, process maps, data mappings, interface specifications, configuration documents, test scripts, validation evidence, or deployment materials.
Experience collaborating with quality, laboratory, operational, and technical delivery teams to investigate requirements, resolve issues, or implement a solution.
Ability to travel as needed based on business and role requirements; travel can range from 80–100%.
Legally authorized to work in the U.S. without the need for employer sponsorship, now and in the future.
Knowledge of quality-domain processes including deviations and nonconformances, investigations, CAPA, change control, complaints, audits, inspection readiness, supplier quality, batch disposition and release, review by exception, and quality risk management.
Hands-on functional, configuration, integration, testing, or support experience with eQMS/QMS platforms and digital-quality workflows.
Understanding of LIMS, assays, stability, specifications, OOS/OOT workflows, laboratory instruments, deviation and CAPA analysis, and connections among QA, QC, manufacturing, and release.
Ability to identify source systems, interpret quality and laboratory records, document mappings and interfaces, investigate data-quality issues, and contextualize information across quality, laboratory, manufacturing, equipment, and process domains.
Ability to produce accurate requirements, design documents, test scripts, defect records, validation evidence, controlled-change documentation, and deployment materials, and follow issues through resolution.
Ability to communicate quality or laboratory problems to business users and document them clearly for developers, data engineers, laboratory-systems specialists, validation leads, or testers.
Working understanding of GxP/GMP, data integrity, electronic records and signatures, controlled change, validation or risk-based assurance, audit trails, and traceability.
Ability to assess recurring events, trends, and potential root causes, and evaluate whether analytics or AI outputs are supported by reliable data, appropriate controls, and human review.

Nice To Haves

Experience implementing or supporting eQMS/QMS platforms and digital workflows for deviations, CAPA, change control, complaints, audits, supplier quality, training, document control, or quality risk management.
Experience with LIMS, laboratory execution or data systems, chromatography data systems, stability management, assays, specifications, OOS/OOT workflows, or laboratory-instrument integration.
Experience integrating quality, laboratory, manufacturing, equipment, and process data and relating it to products, materials, batches, methods, specifications, instruments, quality events, and release decisions.
Experience supporting batch disposition, product release, review by exception, annual product quality review, continued process verification, or inspection-readiness capabilities.
Exposure to GxP computer system validation, risk-based software assurance, data-integrity controls, electronic records and signatures, controlled change, audit trails, and end-to-end traceability.
Experience applying analytics or AI to Quality, such as AI-assisted investigation and root-cause analysis, anomaly or trend detection, predictive quality, or quality decision support.
Understanding of human-in-the-loop review, model and data governance, explainability, monitoring, and control requirements for AI-enabled GxP workflows.
Experience with drug substance, drug product, biologics, sterile manufacturing, medical devices, technology transfer, or laboratory operations.
Relevant quality, eQMS/QMS, LIMS, validation, cloud, data, AI, or Agile certification.

Responsibilities

Assess quality and laboratory workflows, user needs, system interfaces, instrument and equipment data, and current-state pain points through interviews, workshops, process observation, and data review.
Document process flows, user stories, functional requirements, data mappings, interface requirements, quality-system controls, and acceptance criteria for digital quality solutions.
Support the design and implementation of quality-domain capabilities, including deviations and nonconformances, investigations, CAPA, change control, complaints, audits and inspection readiness, supplier quality, batch disposition and release, review by exception, and quality risk management.
Design and improve digital-quality workflows using eQMS/QMS platforms, including workflow configuration, records management, approvals, escalation paths, effectiveness checks, reporting, and integration with adjacent enterprise systems.
Connect QA/QC and laboratory processes across LIMS, eQMS/QMS, MES, ERP, chromatography and other laboratory data systems, and relevant manufacturing platforms; support assays, stability programs, OOS/OOT traceability, deviation and CAPA analysis, and batch-review workflows.
Develop and review quality and laboratory data models, source-to-target mappings, data-quality rules, and contextualized datasets relating quality events to products, materials, batches, methods, specifications, instruments, equipment, and process conditions.
Work with solution architects and engineers on interface specifications, APIs, laboratory-instrument connectivity, and secure movement of quality, laboratory, manufacturing, equipment, and process data across site and enterprise environments.
Configure or prototype solution components where appropriate to experience and engagement needs, and document design decisions for review by quality, technical, and client leads.
Prepare and execute functional and integration test scripts, record defects, support resolution and retesting, and maintain traceability between requirements, risks, controls, and test evidence.
Support deployment readiness, controlled change, user training, hypercare, and handover by preparing documentation and responding to issues from quality and laboratory users.
Partner with client quality and validation teams to prepare or review documentation addressing GxP/GMP, data integrity, electronic records and signatures, controlled change, validation or risk-based assurance, audit trails, and end-to-end traceability.
Integrate and contextualize quality, laboratory, manufacturing, equipment, and process data to identify recurring events, detect trends, support root-cause analysis, and improve quality decision-making.
Contribute to governed AI applications for Quality, including AI-assisted investigations and root-cause analysis, anomaly and trend detection, predictive quality, and decision support, with appropriate human-in-the-loop review, governance, and controls.
Communicate progress, risks, dependencies, and recommended next steps to client counterparts and engagement leaders; coordinate defined tasks with junior colleagues when needed.