Analytics Lead (Global Manufacturing Analytics)

Job Description

As the Analytics Lead, you will lead the evolution of the Control Tower as the global platform for operational visibility, decision intelligence, and execution, applying analytics, AI, and decision science to improve productivity, quality, operational risk management, and cost performance.

You will combine analytics leadership, digital product management, and change leadership to build, scale, and continuously improve Manufacturing Analytics products that enable enterprise decision-making across the global manufacturing network.

Working closely with Manufacturing, Engineering, and cross-functional teams, you will translate business priorities into scalable global analytics solutions, define executive-ready dashboards and KPI frameworks, and drive enterprise adoption. You will serve as the bridge between senior business stakeholders and technical delivery teams, ensuring analytics solutions deliver measurable business value and become an integral part of the Manufacturing Operating System.

Responsibilities:

• Own the Manufacturing Control Tower insight portfolio, defining the product roadmap, prioritizing capabilities, and continuously evolving analytics products that improve operational visibility, decision intelligence, and business execution.
• Lead the design and delivery of executive-ready dashboards, KPI frameworks, and analytics solutions, ensuring trusted metrics, intuitive user experience, and actionable insights that support strategic and operational decision-making.
• Translate business priorities into scalable global analytics solutions by partnering with Manufacturing, Engineering, and cross-functional teams to define requirements, prioritize opportunities, and deliver high-impact digital capabilities.
• Apply business analytics, statistics, and emerging AI/ML capabilities to identify operational opportunities, enhance decision-making, and integrate forecasting, scenario modeling, and predictive insights into analytics products.
• Drive enterprise adoption and value realization through stakeholder engagement, communication, training, and change management, ensuring analytics products become embedded in day-to-day operations and management routines.
• Continuously improve the analytics portfolio by monitoring product adoption, user feedback, business outcomes, and emerging technologies, while promoting best practices and standardization across the global manufacturing network.

Qualifications

• Bachelor's or Master's Degree in Data Analytics, Data Science, Statistics, Engineering, Computer Science, Business Analytics, or a related discipline, with 8+ years of experience in analytics, business intelligence, digital products, or manufacturing analytics.
• Strong analytics and technical foundation, with hands-on experience designing executive dashboards, defining KPI frameworks, and applying statistics, business analytics, and modern AI/ML capabilities to solve business problems. Familiarity with enterprise analytics platforms such as Power BI, Spotfire, Tableau, or similar tools.
• Product and business mindset, with experience translating business priorities into scalable analytics solutions, managing product roadmaps or digital solutions, and balancing user needs with business value.
• Excellent communication and stakeholder management skills, with the ability to engage senior business leaders, translate business requirements into technical solutions, and collaborate effectively with software engineers, data engineers, and data scientists to deliver enterprise-scale capabilities.
• Strong leadership and change management experience, with a proven track record of leading cross-functional initiatives, driving enterprise adoption, and embedding analytics into operational decision-making and business processes.
• Experience in manufacturing, supply chain, quality, or industrial engineering.
• PMP or Scrum Master certification preferred, with proven experience managing large-scale, enterprise-level projects.
• Familiarity with Industry 4.0, cloud platforms, MES, or digital transformation initiatives.