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EY
Life Sciences Supply Chain Manufacturing Ops & AI Transformation Delivery- Senior Manager
Source: National Labor Exchange
EY
Life Sciences Supply Chain Manufacturing Ops & AI Transformation Delivery - Senior
Source: National Labor Exchange
EY
Life Sciences Supply Chain Manufacturing Ops & AI Transformation Delivery- Senior Manager
Source: National Labor Exchange
EY
Life Sciences Supply Chain Manufacturing Ops & AI Transformation Delivery- Manager
Source: National Labor Exchange
EY
Life Sciences Supply Chain Manufacturing Ops & AI Transformation Delivery- Senior Manager
Source: National Labor Exchange
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Job ID #79734
EY
Life Sciences Supply Chain Manufacturing Ops & AI Transformation Delivery- Manager
location_on
Kansas City, MO
description
Summary
Location: Anywhere in Country
At EY, we're all in to shape your future with confidence.
We'll help you succeed in a globally connected powerhouse of diverse teams and take your career wherever you want it to go. Join EY and help to build a better working world.
Role Snapshot
Client-facing Life Sciences manufacturing Manager who leads technology-enabled transformation workstreams that improve plant performance, quality, compliance, and supply reliability. The role combines practical manufacturing knowledge with digital, data, AI, and delivery skills to turn operational needs into solutions that work in regulated environments.
The Opportunity
As a Manager in Supply Chain Manufacturing, you will work with pharmaceutical, biotechnology, and medical-device manufacturers to improve how production, quality, laboratory, engineering, and technology teams operate together. You will lead defined workstreams from assessment and requirements through solution design, implementation, testing, adoption, and stabilization.
This is a techno-functional delivery role. You will facilitate decisions with client teams, translate plant-floor needs into actionable requirements, coordinate functional and technical specialists, and take ownership of the quality and progress of your workstream. You will contribute to broader program planning and value realization while working with senior engagement leaders on cross-program decisions and commercial matters.
Your key responsibilities
In this role, you will:
+ 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; escalate 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.
Skills and attributes for success
You will bring:
+ Practical understanding of Life Sciences manufacturing and the connections among production, quality, laboratory operations, engineering, and supply chain.
+ The ability to turn operational problems into clear workflows, functional requirements, user stories, data needs, interface requirements, and testable acceptance criteria.
+ Working knowledge of manufacturing systems and IT/OT data flows, with enough technical fluency to collaborate effectively with automation engineers, architects, data engineers, developers, and cybersecurity teams.
+ Familiarity with batch and equipment data, data contextualization, APIs, historians, and industrial connectivity patterns relevant to the solution being delivered.
+ Sound judgment about when analytics or AI is useful, what data and controls it requires, and how people will use its outputs in manufacturing or quality workflows.
+ Strong workshop facilitation, structured problem-solving, client communication, team coordination, and delivery-risk management skills.
To qualify for the role, you must have:
+ 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%.
Ideally, you'll also have:
+ Experience with drug substance, drug product, biologics, sterile manufacturing, medical devices, or clinical-to-commercial scale-up.
+ Delivery experience with MES/MOM, electronic batch records, recipe management, connected-worker tools, industrial analytics, or manufacturing data platforms.
+ Familiarity with ISA-88/IEC 61512, ISA-95/IEC 62264, OPC UA/IEC 62541, MQTT/Sparkplug, or unified-namespace approaches as relevant to client systems.
+ Awareness of OT cybersecurity practices informed by ISA/IEC 62443 or NIST SP 800-82.
+ Familiarity with Process Analytical Technology (PAT) and continuous improvement practices, including the use of manufacturing data to monitor process performance, identify variability, and improve quality, throughput, and operational performance.
+ Experience supporting computer system validation or risk-based computer software assurance where applicable to the regulated product and system.
+ Experience with multi-site deployments, plant modernization, ...
At EY, we're all in to shape your future with confidence.
We'll help you succeed in a globally connected powerhouse of diverse teams and take your career wherever you want it to go. Join EY and help to build a better working world.
Role Snapshot
Client-facing Life Sciences manufacturing Manager who leads technology-enabled transformation workstreams that improve plant performance, quality, compliance, and supply reliability. The role combines practical manufacturing knowledge with digital, data, AI, and delivery skills to turn operational needs into solutions that work in regulated environments.
The Opportunity
As a Manager in Supply Chain Manufacturing, you will work with pharmaceutical, biotechnology, and medical-device manufacturers to improve how production, quality, laboratory, engineering, and technology teams operate together. You will lead defined workstreams from assessment and requirements through solution design, implementation, testing, adoption, and stabilization.
This is a techno-functional delivery role. You will facilitate decisions with client teams, translate plant-floor needs into actionable requirements, coordinate functional and technical specialists, and take ownership of the quality and progress of your workstream. You will contribute to broader program planning and value realization while working with senior engagement leaders on cross-program decisions and commercial matters.
Your key responsibilities
In this role, you will:
+ 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; escalate 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.
Skills and attributes for success
You will bring:
+ Practical understanding of Life Sciences manufacturing and the connections among production, quality, laboratory operations, engineering, and supply chain.
+ The ability to turn operational problems into clear workflows, functional requirements, user stories, data needs, interface requirements, and testable acceptance criteria.
+ Working knowledge of manufacturing systems and IT/OT data flows, with enough technical fluency to collaborate effectively with automation engineers, architects, data engineers, developers, and cybersecurity teams.
+ Familiarity with batch and equipment data, data contextualization, APIs, historians, and industrial connectivity patterns relevant to the solution being delivered.
+ Sound judgment about when analytics or AI is useful, what data and controls it requires, and how people will use its outputs in manufacturing or quality workflows.
+ Strong workshop facilitation, structured problem-solving, client communication, team coordination, and delivery-risk management skills.
To qualify for the role, you must have:
+ 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%.
Ideally, you'll also have:
+ Experience with drug substance, drug product, biologics, sterile manufacturing, medical devices, or clinical-to-commercial scale-up.
+ Delivery experience with MES/MOM, electronic batch records, recipe management, connected-worker tools, industrial analytics, or manufacturing data platforms.
+ Familiarity with ISA-88/IEC 61512, ISA-95/IEC 62264, OPC UA/IEC 62541, MQTT/Sparkplug, or unified-namespace approaches as relevant to client systems.
+ Awareness of OT cybersecurity practices informed by ISA/IEC 62443 or NIST SP 800-82.
+ Familiarity with Process Analytical Technology (PAT) and continuous improvement practices, including the use of manufacturing data to monitor process performance, identify variability, and improve quality, throughput, and operational performance.
+ Experience supporting computer system validation or risk-based computer software assurance where applicable to the regulated product and system.
+ Experience with multi-site deployments, plant modernization, ...
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