Vice President of Digital Insights & Artificial Intelligence, Quadient

• Master’s degree or PhD in Computer Science, Data Science, Artificial Intelligence, Machine Learning, Engineering, or a related field
• Executive education or certifications in AI strategy, digital transformation, or innovation (e.g., MIT, Stanford, INSEAD programs)
• Certifications in cloud platforms (AWS, Azure, GCP) and data governance frameworks are a plus
• 8+ years of experience in data, analytics, AI, or IT platform leadership roles
• Proven track record of designing and delivering enterprise platforms for data and analytics
• Demonstrated success in deploying AI, automation, and predictive analytics initiatives that drove measurable business outcomes
• Strong knowledge of enterprise architecture, data governance, and platform delivery methodologies (Agile/DevOps)
• Machine learning, deep learning, NLP, computer vision
• Data engineering, big data platforms, and analytics
• AI/ML model lifecycle management (MLOps)
• Cloud-native architectures and scalable AI infrastructure
• Strong understanding of emerging technologies (e.g., generative AI, edge AI, synthetic data)
• Ability to translate complex AI capabilities into business value
• Experience developing and executing digital intelligence strategies aligned with corporate goals
• Strong financial acumen and experience managing large budgets and vendor ecosystems
• Familiarity with industry-specific use cases (e.g., predictive analytics, automation, personalization)
• Visionary leadership with the ability to inspire and mobilize cross-functional teams
• Excellent stakeholder engagement skills, including C-suite and board-level communication
• Experience in change management and fostering a data-driven culture
• Strong presentation and storytelling skills to communicate AI impact
• High emotional intelligence and adaptability
• Ethical mindset and commitment to responsible AI
• Collaborative and inclusive leadership style
• Resilience and ability to navigate ambiguity and complexity

Desirable

• We are seeking a highly capable and strategic VP Digital Insights and Artificial Intelligence to lead on own the strategy, implementation, and governance of data, analytics and AI platform architecture across the organization
• This newly created role is responsible for shaping the company’s approach to information management, enterprise data management, which includes data governance, data quality and data management; analytics, predictive analytics, and AI — while also ensuring the design, delivery, and continuous improvement of the underlying technology platforms that enable these capabilities
• This leader will partner with business stakeholders, IT, and data science teams to identify high-value opportunities, deliver innovative and responsible AI solutions, and build a robust, scalable architecture that supports insight generation, process optimization, and automation
• Reports to: Directly reporting to the CIO
• Define and lead the enterprise-wide Digital Insights & AI Platform Strategy, ensuring alignment with business priorities and long-term technology roadmaps
• Establish governance frameworks for data, analytics, and AI to ensure quality, security, and ethical use
• Drive adoption of AI, automation, and analytics solutions across business functions to maximize ROI and efficiency
• Lead the development and maintenance of information management and enterprise data management frameworks to ensure data quality, consistency, and availability
• Oversee data integration, taxonomy, metadata management, and data stewardship initiatives
• Ensure proper architecture and tooling for data pipelines, data lakes, and enterprise reporting platforms
• IT Platform Architecture & Delivery
• Own the design, delivery, and evolution of enterprise technology platforms that enable data, analytics, and AI
• Define the technical architecture (data, application, integration, and cloud architecture) to support business needs, scalability, and resilience
• Partner with IT delivery teams to ensure timely implementation of platform enhancements and upgrades
• Evaluate and select technology solutions (BI tools, ML platforms, automation frameworks) that align with the enterprise architecture and future-proof the business
• Build and partner on advanced analytics and business intelligence capabilities to deliver actionable insights
• Develop predictive and prescriptive analytics use cases that inform strategic decisions and improve operational outcomes
• Champion self-service analytics and empower business teams to access and use data confidently
• Identify, evaluate, and deliver AI initiatives including:
• Conversational AI (e.g., chatbots, virtual assistants)
• Intelligent Automation (RPA + AI-driven decisioning)
• Machine Learning and Predictive Models for forecasting and optimization
• Collaborate with product, operations, and technology teams to embed AI into products, services, and workflows
• Drive process optimization initiatives using AI insights to reduce friction and improve efficiency
• Act as a trusted advisor to business and IT stakeholders, identifying opportunities where AI and analytics can create business value
• Build strong relationships with internal and external partners (vendors, technology providers, consultants) to accelerate capability building
• Lead change management efforts to drive adoption of digital intelligence solutions and foster a data-driven culture
• Support the building of high-performing team of data analysts, data scientists, solution architects, and AI/automation specialists
• Develop and deliver education and training programs on data literacy, analytics, and AI best practices
• Stay abreast of emerging trends and technologies in AI, machine learning, cloud platforms, and analytics to inform strategic decisions
• Delivery of scalable, secure, and high-performing technology platforms supporting analytics and AI
• Increased data quality and availability across business functions
• Successful deployment and adoption of AI and automation initiatives
• Demonstrated business value from predictive and prescriptive analytics use cases
• Improved collaboration between business and IT teams on data-driven projects
• Enhanced organizational data literacy and digital intelligence maturity