Life Sciences Manufacturing & AI Transformation Manager

EY

Detroit (MI)

Remote

USD 128,000 - 257,000

Full time

6 days ago

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Benefits offered by this job

Medical and dental coverage

401(k) plan

Paid time off

Job summary

EY is seeking a Client-facing Life Sciences Manufacturing Manager to lead technology-enabled transformations that improve plant performance, quality, compliance, and supply reliability in regulated environments.

You will guide workstreams from assessment through solution design, deployment, and stabilization, coordinating with architecture, automation, and cybersecurity specialists while engaging senior leaders on program decisions and commercial matters.

Qualifications

Bachelor’s degree in engineering, life sciences, manufacturing, supply chain, information systems, business, or related discipline.
At least 7 years of relevant Life Sciences manufacturing, manufacturing technology, or related field.
Experience leading client-facing manufacturing/digital/ data workstreams through design and at least one deployment.
Experience in pharmaceutical/biotech/medical-device regulated environments.
Translate manufacturing needs into process, data, and testing deliverables.
Understanding of GxP, data integrity, change-control, and validation requirements.

Responsibilities

Lead client-facing workstreams in Life Sciences manufacturing transformation with defined plans, deliverables, risks, and outcomes.
Assess current-state production, quality processes, data flows, and site constraints via workshops and data analysis.
Translate priorities (yield, throughput, right-first-time, batch-cycle time) into designs and acceptance criteria.
Develop functional designs for batch execution, eBR, genealogy, and related capabilities.
Coordinate integration across MES/MOM, ERP, LIMS, QMS, historians, SCADA, DCS/PLC, and cloud/edge systems.
Define data mappings, master data needs, interface specs, and data-quality controls for reporting and AI use cases.
Assist analytics/AI use cases by assessing data readiness and workflow fit with proper oversight.
Ensure GxP validation and risk-based assurance in deliverables; support testing, cutover, and handover.