Martijn Pirozzi

Lead enterprise AI strategy and execution across 14 business units, 30+ brands, and 34 North American locations for a ~$1.5B manufacturer, driving scalable AI adoption, operational efficiency, and measurable business value. - Own enterprise AI portfolio, defining strategy, prioritization, and ROI-driven use case roadmap aligned with corporate objectives - Built and lead a lean, high-impact AI function from the ground up, operating as a hybrid of executive leader, strategist, and hands-on contributor - Delivered production-grade AI solutions on Azure (Functions, Apps, Fabric) leveraging LLM-based development to accelerate time-to-value - Established enterprise data and AI foundations, advising IT on architecture (Fabric/OneLake) to enable cross-channel insights (e-commerce, B2B, retail, wholesale) - Led enterprise AI vendor strategy, including MuleSoft ($1.6M contract) and Salesforce/Agentforce integrations, ensuring scalable and cost-effective platform adoption - Drove AI and integration adoption across the organization, embedding MuleSoft and Salesforce AI capabilities into core business processes - Spearheaded AI enablement programs (AI Champions, Lunch & Learn, internal communities) to drive cultural transformation and adoption at scale - Delivered AI initiatives across customer service, supply chain, manufacturing, and commercial functions, including secure enterprise LLM deployment, RAG architectures, and custom ML solutions - Played a key role in 2 acquisitions, establishing AI and integration capabilities and delivering measurable value within the first 90 days

Eviden is a carve-out of the successful business units. Clients such as: Airbus, Satair, Teijin, Dutch & Flemish Government • Worked on AI Strategies, Enterprise Frameworks, Use Case Funnels, and major data migrations. • Effective RFI/RFP responses, (pre-)sales presentations, and relationship building. • Developed CxO-level partnerships and grew accounts through my ability to understand the needs and align offerings. • Managed international stakeholders from the US, France, China, Korea, Singapore, Denmark, and the Netherlands. • Facilitated cross-departmental client use case prioritization sessions to identify Proof-Of-Concept candidates aligned with business requirements, and strategy. • Managed large Agile Transformation projects with up to 15 direct reports, focusing on data lakes, machine learning, and dashboarding solutions using Azure tools, Google tools, VMs, Databricks, and PowerBI. • Supported a $4M+ Supply Chain Enhancement Program for a Fortune 125 company, reducing response time from 24 hours to 2 minutes and increasing sales by 18% through a machine learning solution that integrated SAP APIs and GCP tools. • Architected and implemented over 30 custom RPA processes in UiPath, optimizing operational efficiency. • Architected a subscription-based business model through a Minimum Viable Product (MVP) of an API-driven service platform on Google Cloud including local middleware, for B2B (manufacturer-to-airlines), providing direct insights into inventory and prices.

• Engineered an algorithm, in Python and CPLEX (IBM), addressing complex routing challenges for distributing perishable goods to comply with new EU regulations limiting city-center access to electric trucks. • The mathematical model solves non-linear problems while optimizing miles per battery charge using 14 parameters and 5 decision variables such as weight factors, fresh/frozen demand, engine efficiency, delivery windows, and serving time.

Focused on (digital) manufacturing, Internet of Things, Asset Management, Digital Twins, Robotics, Simulations, Product Life Cycles, etc. Top courses: - Asset Management - Operations Management and Control - Operations Modelling and Simulation - Inventory Management - Facility Design and Planning #49th ranked Faculty of Economics and Business, #76th overall globally (US News, 2022) Designed and developed an algorithm for my double master thesis to solve a non-deterministic polynomial-time hardness problem. Written in Python with CPLEX (IBM) optimizer. Thesis title: "Load-Dependent Discharging for an Electric Vehicle Routing Problem"

#49th ranked Faculty of Economics and Business, #76th overall globally (US News, 2022) Designed and developed an algorithm for my double master thesis to solve a non-deterministic polynomial-time hardness problem. Written in Python with CPLEX (IBM) optimizer. Thesis title: "Load-Dependent Discharging for an Electric Vehicle Routing Problem"

Bridge year to get calculus and statistics on par for the double degree program + following some technology focused courses. Research Paper title: "Coopetition in Dutch healthcare: involvement of parties in designing healthcare"

Minor Advanced International Finance & Accounting Minor International Industrial Entrepreneurship I & II