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

EY•Hartford, DC

4d•$97,300 - $202,600•Remote

About The Position

Client-facing Life Sciences manufacturing professional who helps design, build, test, and deploy digital solutions for regulated plant operations. The role combines practical knowledge of manufacturing processes with hands-on skills in manufacturing systems, industrial data, integration, analytics, and AI-enabled workflows. As a Senior in Supply Chain Manufacturing, you will work with pharmaceutical, biotechnology, and medical-device clients to connect production, quality, laboratory, engineering, and supply chain needs with deployable technology. You will contribute across the delivery lifecycle, from plant and system assessments through requirements, solution design, configuration support, testing, deployment, adoption, and stabilization. You will work directly with operators, engineers, quality teams, IT and OT specialists, data teams, and technology providers. You will own assigned technical and functional deliverables, help resolve implementation issues, and make clear recommendations to your workstream lead. The role calls for someone who can examine a shop-floor workflow, trace the data and systems behind it, and turn what they learn into a design or testable requirement.

Requirements

A bachelor’s degree in engineering, life sciences, manufacturing, information systems, computer science, supply chain, or a related discipline.
At least 3 years of relevant experience in Life Sciences manufacturing, manufacturing systems, automation, industrial data, systems implementation, technology consulting, or a related field.
Experience working with manufacturing or quality processes in a pharmaceutical, biotechnology, medical-device, or comparably regulated environment.
Experience producing technical or functional delivery artifacts, such as requirements, process maps, data mappings, interface specifications, configuration documents, test scripts, or deployment materials.
Experience collaborating with both operational stakeholders and technical delivery teams to investigate requirements, resolve issues, or implement a solution.
Ability to travel as needed based on business and role requirements. Travel can range from 80-100%.

Nice To Haves

Experience with MES/MOM, electronic batch records or eDHRs, recipe management, LIMS, QMS, historians, SCADA, DCS/PLC, connected-worker solutions, or industrial data platforms.
Experience examining manufacturing data from more than one source and relating it to assets, materials, products, orders, recipes, batches, or quality events.
Familiarity with ISA-88/IEC 61512 batch concepts, ISA-95/IEC 62264 manufacturing information models, or industrial connectivity approaches such as OPC UA and MQTT/Sparkplug.
Exposure to GxP computer system validation, risk-based software assurance, data-integrity controls, electronic records, or OT cybersecurity considerations relevant to the system being delivered.
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 analytics or AI use cases in manufacturing or quality, such as process monitoring, predictive maintenance, deviation investigation, or decision support.
Experience with drug substance, drug product, biologics, sterile manufacturing, medical devices, or technology transfer.
Relevant platform, cloud, data, automation, Agile, or manufacturing certification.

Responsibilities

Assess manufacturing and quality workflows, user needs, system interfaces, equipment data, and current-state pain points through site observations, interviews, workshops, and data review.
Document process flows, user stories, functional requirements, data mappings, interface requirements, controls, and acceptance criteria for digital manufacturing solutions.
Support the design and implementation of capabilities such as manufacturing execution, electronic batch records and electronic device history records (eDHRs), recipe and routing management, batch and unit genealogy, review by exception, connected-worker workflows, and plant performance reporting.
Trace information across relevant systems, including MES/MOM, ERP, LIMS, QMS, historians, SCADA, DCS/PLC, and asset-management platforms; identify data gaps, inconsistent definitions, and integration dependencies.
Develop and review equipment and batch hierarchies, source-to-target mappings, data-quality rules, and contextualized datasets with manufacturing, automation, and data specialists.
Work with solution architects and engineers on interface specifications, APIs, industrial connectivity, and the movement of data between plant, edge, and enterprise environments.
Configure or prototype solution components where appropriate to your experience and the engagement, and document design decisions for review by technical and client leads.
Prepare and execute functional and integration test scripts, record defects, support resolution and retesting, and maintain traceability between requirements and test evidence.
Support deployment readiness, cutover, user training, hypercare, and handover by preparing clear technical documentation and responding to issues from plant users.
Partner with client quality and validation teams to prepare or review applicable documentation concerning GxP, data integrity, electronic records, change control, and computer system validation or risk-based assurance.
Contribute to analytics and AI use cases by assessing source-data quality, defining manufacturing context, checking outputs against operational workflows, and documenting where human review is needed.
Communicate progress, risks, dependencies, and recommended next steps to client counterparts and engagement leaders; coordinate defined tasks with junior colleagues when needed.