Digital Manufacturing Data & AI Consultant

Salary: $54, per year

• We require at least 3 years of experience in process excellence, process redesign, or management consulting.
• We require at least 1 year of experience using AI-assisted analytics, visualization, and generative AI tools for content creation and low-fidelity user interfaces.
• We require at least 1 year of experience integrating AI and automating business process design.
• We require at least 1 year of experience delivering project work in a consulting environment or industry experience in one relevant domain, such as Life Sciences, Consumer Goods Industrial, Energy, Utilities, or Chemical and Natural Resources.
• We require a bachelors degree or equivalent, which may be met through 12 years of work experience.
• If you hold an associate degree, we require at least 6 years of work experience.
• Travel is required for this role and may be up to 75%.
• Preferred qualifications include familiarity with process mapping or process modeling tools.
• Preferred qualifications include strong analytical ability and the skill to communicate complex findings in clear business language and structured recommendations.
• Preferred qualifications include client-facing consulting or advisory experience.
• Preferred qualifications include fluent, independent use of AI tools, including building agents, to produce higher-quality solutions to business problems.
• Preferred qualifications include embedding AI design principles into process specifications, including agent behavior, autonomy levels, and handoffs.
• Preferred qualifications include identifying where agentic AI can transform specific client process steps and explaining the design implications.
• Preferred qualifications include using AI-assisted analytics, visualization, and benchmarking tools to ground future-state designs.
• Preferred qualifications include demonstrated continuous learning with emerging AI tools.
• Preferred qualifications include expertise in big data technologies, ontology, and AI/ML frameworks.
• Preferred qualifications include the ability to analyze data and translate findings into structured recommendations.
• Preferred qualifications include understanding of modern data and AI strategy, including data mesh, data products, semantic layers, and how these foundations enable AI-driven manufacturing use cases.
• Preferred qualifications include familiarity with digital manufacturing platforms, factory IT/OT, digital twins, and advanced automation, with experience architecting manufacturing use cases.
• Preferred qualifications include understanding of GxP and regulatory considerations in pharma manufacturing and how they shape data and AI solutions.

• We use relevant AI tools across all tasks and deliverable creation, including building low-code proofs of concept, agents, and related artifacts.
• We analyze clients current-state processes, technology tools, and organizational structures to define a data- and AI-driven future state.
• We design future-state process specifications that include AI integration points, operating model changes, human-machine interaction requirements, and workforce adoption approaches for Life Sciences manufacturing and quality functions.
• We conduct process analysis and support the delivery of digital and platform solutions across operations.
• We build analytical frameworks and data-driven assessments using AI-assisted visualization and analysis tools.
• We develop change-impact assessments using AI-assisted organizational analysis tools.
• We apply industry and functional expertise to review and improve reinvention designs and functional playbook content.
• We contribute to the reference library and keep our domain knowledge current through continuous learning.
• We apply AX Design principles when defining or reviewing AI integration, including agent behavior, autonomy, and human handoffs.
• We apply generative AI and agent-based modeling to speed up scenario planning, exception management, and autonomous decision-making.
• We define and implement AI-enabled supply chain control towers for real-time visibility, risk sensing, and proactive disruption management.
• We collaborate with clients to deploy predictive maintenance, digital twins, and intelligent automation across manufacturing and distribution networks.
• We translate business challenges into AI and machine learning use cases, build proofs of concept, and scale solutions enterprise-wide.
• We support data strategy, governance, and architecture to ensure high-quality, AI-ready supply chain data across ERP, PLM,…