Life Sciences Supply Chain Manufacturing Ops & AI Transformation Delivery- Senior Manager

Location: Anywhere in Country

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Client-facing Life Sciences manufacturing transformation leader accountable for shaping and delivering technology-enabled programs that improve manufacturing performance, quality, compliance, and supply reliability. The role combines regulated plant-floor expertise with data, AI, automation, and disciplined program delivery.

The Opportunity

As a Senior Manager in Supply Chain Manufacturing, you will lead transformation programs for pharmaceutical, biotechnology, and medical-device manufacturers, from defining the operational problem and value case through solution design, implementation, adoption, stabilization, and measurable results. You will work across manufacturing, quality, laboratory, engineering, supply chain, and technology teams to connect plant operations with enterprise systems and data.

This is a techno-functional delivery role. You will need the credibility to redesign manufacturing processes and operating models, and the fluency to direct teams delivering manufacturing execution, automation, integration, data, and AI solutions. You will remain accountable for delivery quality, risk, client relationships, and outcomes in regulated environments. “The Life Sciences focus reflects the practice’s emphasis on connected manufacturing and quality workflows across process, batch, and discrete operations, including electronic batch records, electronic device history records (eDHRs), traceability, and integration across plant and enterprise systems.”

Your key responsibilities

In this role, you will lead complex client engagements while balancing operational improvement, technology delivery, quality requirements, and commercial commitments. You will:

• Lead end-to-end Life Sciences manufacturing transformations, from assessment and mobilization through design, deployment, stabilization, and value realization.

• Build trusted relationships with senior manufacturing, quality, MS&T, engineering, supply chain, digital, and IT/OT stakeholders; establish governance and drive timely decisions.

• Translate priorities such as yield, throughput, right-first-time execution, deviation reduction, batch-cycle time, asset reliability, and supply continuity into practical workplans and outcome measures.

• Direct multidisciplinary teams across manufacturing process design, MES/MOM, automation, data engineering, AI, architecture, integration, quality, change management, testing, and deployment.

• Lead solution and process design for batch and discrete execution, electronic batch records, electronic device history records (eDHRs), recipes and routings, material and product genealogy, review by exception, maintenance, quality workflows, and plant performance management.

• Guide integration across MES/MOM, ERP, LIMS, QMS, historians, SCADA, DCS/PLC, asset-management systems, and relevant cloud or edge platforms.

• Establish trusted manufacturing data foundations through appropriate data models, asset and process context, master data, metadata, lineage, governance, and secure IT/OT connectivity.

• Shape analytics and AI use cases, such as process monitoring, predictive maintenance, deviation investigation support, digital twins, and decision support; assess their value, data readiness, workflow fit, and risks before scaling.

• Partner with client quality and validation teams to incorporate applicable GxP controls, data integrity, electronic-record requirements, change control, and risk-based assurance into delivery plans. The applicable controls will depend on the product, system, and intended use.

• Manage scope, schedule, budget, staffing, dependencies, quality, risks, issues, and contractual commitments; guide testing, cutover, training, adoption, and operational handover.

• Connect digital solutions to daily management, operational excellence, workforce capability building, and sustained process improvement.

• Ability to create clarity and alignment across distributed teams, motivate people through complex delivery challenges, and maintain accountability without becoming the bottleneck for decisions.

• People leadership and talent-development capability, including coaching, delegation, performance feedback, conflict resolution, succession planning, and building teams with the right mix of functional, technical, and industry skills.

• Develop Managers and delivery teams, contribute reusable methods and lessons learned, and identify appropriate follow‑on opportunities with account teams.

Skills and attributes for success

Success in this role requires the ability to connect regulated manufacturing realities with scalable technology delivery. You will bring:

• Strong knowledge of Life Sciences manufacturing processes and the relationship between production, quality, laboratory operations, engineering, and supply.

• Techno‑functional leadership that earns the confidence of plant teams while providing clear direction to architects, engineers, developers, data scientists, and cybersecurity specialists.

• Working knowledge of industrial data and integration patterns, including OPC UA (IEC 62541), MQTT/Sparkplug, APIs, historians, asset and batch contextualization, and unified‑namespace approaches; able to evaluate how these patterns support secure, reliable data exchange across OT and enterprise systems.

• Sound judgment about where analytics or AI can improve a workflow, what evidence is needed to support its use, and where human review and quality oversight must remain.

• Executive communication, structured problem‑solving, facilitation, negotiation, and the ability to make decisions under ambiguity.

• Commercial and delivery discipline across estimates, staffing, engagement economics, change control, risk management, and value realization.

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.

• No less than 10+ years of relevant experience spanning Life Sciences manufacturing, manufacturing technology, operational excellence, industrial data and AI, technology consulting, or a related field.

• Experience leading complex manufacturing transformation or technology‑enabled improvement initiatives in a pharmaceutical, biotechnology, medical‑device, or comparably regulated environment.

• Experience delivering client‑facing programs through design, implementation, deployment, and stabilization, with accountability for governance, resources, quality, financial performance, and risk.

• Experience leading senior stakeholders and multidisciplinary teams across business, functional, data, and technology workstreams.

• Experience translating manufacturing requirements into process, system, data, integration, security, and technical requirements, with traceability through testing and deployment.

• Practical understanding of GxP manufacturing and the quality, documentation, change‑control, 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.

• Experience leading multi‑site deployments, greenfield or brownfield plant modernization, or manufacturing technology‑transfer initiatives.

• Implementation experience with one or more MES/MOM platforms, electronic batch records and eDHRs, 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, and OT cybersecurity practices informed by ISA/IEC 62443 and NIST SP 800‑82. Exposure to IEC 61131‑3, IEC 61499, CESMII i3X, O‑PAS, or SiLA 2 is a plus where relevant to the client environment.

• Familiarity with Process Analytical Technology (PAT) and continuous‑improvement practices, and their application to manufacturing analytics, process performance, quality, and operational decision‑making.

• Experience with computer system validation or risk‑based computer software assurance, as applicable to the systems and regulated products involved.

• Experience applying AI or advanced analytics to manufacturing or quality workflows with appropriate model governance, monitoring, and human oversight.

• A master’s degree or relevant program‑management, operational‑excellence, cloud, data, or manufacturing‑technology certification.

What we look for

We are looking for a Senior Manager who can move confidently between the plant floor and the executive discussion. The successful candidate will combine Life Sciences manufacturing credibility, quality‑minded judgment, technology and data fluency, commercial awareness, and hands‑on delivery leadership to produce improvements that clients can operate and sustain.

What we offer you

At EY, we harness our collective strength to empower you to shape your future with confidence through professional growth, personal fulfillment and an inclusive culture. Learn more at ey.com/us/careers .

• The salary range for this job is:

• New York City, Boston, and Washington DC Metro Areas, Washington State, and Southern California offices – $180,500 to $374,800

• Bay Area California offices – $188,100 to $390,500

• All other offices locations in the US, including Sacramento – $150,400 to $343,600

• Individual salaries within these ranges are determined through a wide variety of factors including but not limited to education, experience, knowledge, skills and geography. In addition, our Total Rewards package includes medical and dental coverage, pension and 401(k) plans, and a wide range of paid time off options.

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