Senior AI-Driven Life Sciences Manufacturing Delivery

EY

Des Moines (IA)

Remote

USD 100,000 - 178,000

Full time

3 days ago

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Job summary

EY, a global professional services firm, is seeking a Senior in Supply Chain Manufacturing to design, build, test, and deploy digital solutions for regulated plant operations across pharmaceutical, biotechnology, and medical-device clients.

You will own technical and functional deliverables, collaborate with operators, engineers, quality teams, IT and OT specialists, and guide projects from assessments through deployment and stabilization.

Qualifications

Bachelor’s degree in engineering, life sciences, manufacturing, information systems, computer science or related discipline.
Minimum 3 years of Life Sciences manufacturing, manufacturing systems, automation, or related experience.
Experience in pharmaceutical/biotech/medical-device regulated environments.
Proven ability to deliver technical/functional artifacts (requirements, maps, specs, test scripts).
Experience collaborating with both operators and technical delivery teams.
Ability to travel as needed; travel could be 80–100%.

Responsibilities

Assess workflows, user needs, system interfaces, data, and pain points through observations and interviews.
Document process flows, requirements, data mappings, and interface specs for digital manufacturing solutions.
Support design and implementation of MES, eDHRs, recipe and routing management, and plant performance reporting.
Trace information across MES/MOM, ERP, LIMS, QMS, historians, SCADA, DCS/PLC and asset-management platforms.
Develop equipment and batch hierarchies, data-quality rules, and contextual datasets with experts.
Collaborate on interface specs, APIs, and data movement between plant, edge, and enterprise environments.
Configure or prototype solution components and document design decisions.
Prepare and execute functional and integration test scripts; track defects and ensure traceability.
Support deployment readiness, training, hyper-care, and handover with clear technical documentation.
Coordinate with client quality and validation teams on GxP, data integrity and validation concerns.
Contribute to analytics and AI use cases by assessing data quality and manufacturing context.
Communicate progress, risks and next steps to client counterparts and engagement leads.