Life Sciences Manufacturing AI Transformation Lead

EY

Frankfort (KY)

On-site

USD 128,000 - 257,000

Full time

10 days ago

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Benefits offered by this job

Medical and dental coverage

Pension and 401(k)

Paid time off

Job summary

EY is seeking a Manager in Supply Chain Manufacturing to lead techno-functional workstreams in Life Sciences manufacturing, driving digital transformation, data, and AI-enabled improvements in regulated environments.

You will coordinate with MES/MOM, ERP, LIMS, QMS, historians, and OT/IT teams, translate plant-floor needs into actionable requirements, and guide delivery from assessment through deployment, while ensuring quality and compliance across programs.

Qualifications

A bachelor’s degree in engineering, life sciences, manufacturing, supply chain, information systems, business, or a related discipline.
At least 7 years of relevant experience in Life Sciences manufacturing, manufacturing technology, operational excellence, industrial data and AI, technology consulting, or a related field.
Experience leading a client-facing manufacturing, digital, data, or technology workstream through design and at least one implementation or deployment phase.
Experience working in a pharmaceutical, biotechnology, medical-device, or comparably regulated manufacturing environment.
Experience translating manufacturing needs into process, functional, data, integration, or testing deliverables and coordinating business and technical contributors.
Practical understanding of GxP manufacturing and the documentation, change-control, quality, and data-integrity considerations relevant to digital solutions.
Ability to travel as needed based on business and role requirements. Travel can range from 80-100%.

Responsibilities

Lead client-facing workstreams in Life Sciences manufacturing transformation, with clear ownership of plans, deliverables, risks, decisions, and outcomes.
Assess current-state production and quality processes, user needs, system landscapes, data flows, performance gaps, and site constraints through workshops, data analysis, and plant engagement.
Translate priorities such as yield, throughput, right-first-time execution, batch-cycle time, deviation reduction, asset reliability, and supply continuity into process designs, requirements, acceptance criteria, and measurable improvements.
Develop functional designs for relevant capabilities such as batch execution, electronic batch records, recipe management, genealogy, review by exception, connected-worker workflows, maintenance, and performance management.
Coordinate integration requirements across MES/MOM, ERP, LIMS, QMS, historians, SCADA, DCS/PLC, asset-management systems, and cloud or edge platforms, working with architecture, automation, and cybersecurity specialists.
Define and review data mappings, asset and batch context, master-data needs, interface specifications, and data-quality controls needed for reporting, analytics, and AI use cases.
Help deliver analytics and AI use cases, such as process monitoring, predictive maintenance, deviation investigation support, and decision support, by assessing data readiness, workflow fit, evaluation criteria, and human oversight.
Work with client quality and validation teams to reflect applicable GxP, data-integrity, electronic-record, change-control, and validation or risk-based assurance requirements in workstream deliverables.
Oversee configuration activities and lead functional testing, defect resolution, deployment readiness, training, cutover support, hypercare, and handover for your workstream.
Facilitate working sessions across manufacturing, quality, MS&T, engineering, supply chain, IT, OT, data, and technology-vendor teams; elevate decisions and dependencies that affect the broader program.
Manage workstream scope, schedule, resources, quality, and risks; provide clear status updates and contribute to estimates, proposals, and follow-on opportunity shaping.
Coach junior team members, review their work products, and capture reusable requirements, design patterns, and delivery lessons.