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Client-facing Life Sciences quality professional who helps design, build, test, and deploy digital solutions for regulated quality, laboratory, and manufacturing environments. 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 opportunity

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 calls for someone who can examine a quality or laboratory workflow, trace the records, data, instruments, and systems behind it, and translate what they learn into a compliant design or testable requirement.

Your key responsibilities

In this role, you will:

+ 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 spanning 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 that relate 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 the secure movement of quality, laboratory, manufacturing, equipment, and process data across site and enterprise environments.

+ Configure or prototype solution components where appropriate to your experience and the engagement, 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 clear 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.

Skills and attributes for success

To thrive in this role, you should be able to work in depth in at least one quality or laboratory technology area while collaborating across the broader digital-quality ecosystem. You will bring:

+ Quality-domain expertise: Knowledge of deviations and nonconformances, investigations, CAPA, change control, complaints, audits, inspection readiness, supplier quality, batch disposition and release, review by exception, and quality risk management.

+ Digital QMS skills: Hands-on functional, configuration, integration, testing, or support experience with eQMS/QMS platforms and digital-quality workflows.

+ QA/QC and laboratory integration: Understanding of LIMS, assays, stability, specifications, OOS/OOT workflows, laboratory instruments, deviation and CAPA analysis, and the connections among QA, QC, manufacturing, and release.

+ Quality data and integration skills: 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.

+ Delivery discipline: Ability to produce accurate requirements, design documents, test scripts, defect records, validation evidence, controlled-change documentation, and deployment materials, and to follow issues through resolution.

+ Technical communication: Ability to discuss a quality or laboratory problem with a business user and document it clearly enough for a developer, data engineer, laboratory-systems specialist, validation lead, or tester to act on.

+ GxP and quality-system controls: Working understanding of GxP/GMP, data integrity, electronic records and signatures, controlled change, validation or risk-based assurance, audit trails, and traceability.

+ Analytical judgment: Ability to assess recurring events, trends, and potential root causes, and to evaluate whether analytics or AI outputs are supported by reliable data, appropriate controls, and human review.

To qualify for the role, you must have:

+ A 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, Qual...

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Supply Chain Operations - Life Sciences Manufacturing Quality - Senior

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