Senior Life Sciences Manufacturing & AI Delivery Lead

EY

Palo Alto (CA)

Remote

USD 122,000 - 203,000

Full time

4 days ago

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Job summary

EY is seeking a Senior in Supply Chain Manufacturing to design, build, test, and deploy digital solutions for regulated plant operations in Life Sciences. You will connect production, quality, lab, and IT with deployable technology across the delivery lifecycle, collaborating with operators, engineers, and data teams.

You will own deliverables, resolve issues, and translate shop-floor observations into tested requirements, with travel up to 80–100% as needed.

Qualifications

Bachelor's degree in engineering, life sciences, manufacturing, information systems, computer science, supply chain, or related field.
At least 3 years of relevant experience in Life Sciences manufacturing or regulated environments.
Experience with manufacturing or quality processes in pharma, biotech, or medical devices.
Experience producing technical artifacts like requirements, process maps, data mappings, interfaces, or test materials.
Experience collaborating with both operations and technical delivery teams.

Responsibilities

Assess manufacturing and quality workflows, user needs, system interfaces, equipment data, and current-state pain points through site observations, interviews, workshops, and data review.
Document process flows, user stories, functional requirements, data mappings, interface requirements, controls, and acceptance criteria for digital manufacturing solutions.
Support the design and implementation of capabilities such as manufacturing execution, electronic batch records and electronic device history records (eDHRs), recipe and routing management, batch and unit genealogy, review by exception, connected-worker workflows, and plant performance reporting.
Trace information across relevant systems, including MES/MOM, ERP, LIMS, QMS, historians, SCADA, DCS/PLC, and asset-management platforms; identify data gaps, inconsistent definitions, and integration dependencies.
Develop and review equipment and batch hierarchies, source-to-target mappings, data-quality rules, and contextualized datasets with manufacturing, automation, and data specialists.
Work with solution architects and engineers on interface specifications, APIs, industrial connectivity, and the movement of data between plant, edge, and enterprise environments.
Configure or prototype solution components where appropriate to your experience and the engagement, and document design decisions for review by technical and client leads.
Prepare and execute functional and integration test scripts, record defects, support resolution and retesting, and maintain traceability between requirements and test evidence.
Support deployment readiness, cutover, user training, hyper-care, and handover by preparing clear technical documentation and responding to issues from plant users.
Partner with client quality and validation teams to prepare or review applicable documentation concerning GxP, data integrity, electronic records, change control, and computer system validation or risk-based assurance.
Contribute to analytics and AI use cases by assessing source-data quality, defining manufacturing context, checking outputs against operational workflows, and documenting where human review is needed.
Communicate progress, risks, dependencies, and recommended next steps to client counterparts and engagement leaders; coordinate defined tasks with junior colleagues when needed.