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

EY•Hartford, DC

31d•$150,400 - $390,500

About The Position

EY is hiring a client-facing Senior Manager in Supply Chain Manufacturing to shape and deliver technology-enabled transformation programs for pharmaceutical, biotechnology, and medical-device manufacturers. The role spans the full program lifecycle, from defining operational problems and value cases through solution design, implementation, adoption, stabilization, and measurable value realization. It combines regulated plant-floor expertise with data, AI, automation, and disciplined program delivery. The Senior Manager will work across manufacturing, quality, laboratory, engineering, supply chain, and technology teams to connect plant operations with enterprise systems and data. This techno-functional delivery leader is accountable for delivery quality, risk, client relationships, commercial commitments, and outcomes in regulated environments. The work includes connected manufacturing and quality workflows across process, batch, and discrete operations, including electronic batch records, electronic device history records, traceability, and integration across plant and enterprise systems. The role also includes building trusted senior client relationships, leading multidisciplinary and distributed teams, developing Managers and delivery teams, coaching and delegating, and contributing reusable methods and lessons learned. The position may require 80–100% travel based on business and role requirements. The role is advertised for locations anywhere in the country, and EY accepts applications on an ongoing basis.

Requirements

Bachelor’s degree in engineering, life sciences, manufacturing, supply chain, information systems, business, or a related discipline.
At least 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 pharmaceutical, biotechnology, medical-device, or comparably regulated environments.
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 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%.
Strong knowledge of Life Sciences manufacturing processes and the relationship between production, quality, laboratory operations, engineering, and supply.
Techno-functional leadership that can earn plant-team confidence and provide 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.
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 decision-making under ambiguity.
Commercial and delivery discipline across estimates, staffing, engagement economics, change control, risk management, and value realization.

Nice To Haves

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 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.
Master’s degree or relevant program-management, operational-excellence, cloud, data, or manufacturing-technology certification.

Responsibilities

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 operational priorities such as yield, throughput, right-first-time execution, deviation reduction, batch-cycle time, asset reliability, and supply continuity into 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, 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, including data models, asset and process context, master data, metadata, lineage, governance, and secure IT/OT connectivity.
Shape analytics and AI use cases, assess their value, data readiness, workflow fit, and risks, and guide appropriate 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.
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.
Create clarity and alignment across distributed teams, motivate people through complex delivery challenges, and maintain accountability without becoming a decision bottleneck.
Coach and develop people through delegation, performance feedback, conflict resolution, succession planning, and building teams with appropriate 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.