Supply Chain Analytics Manager

Company Description

INFICON is a leading provider of innovative instrumentation, critical sensor technologies, and Smart Manufacturing/Industry 4.0 software solutions that enhance productivity and quality of tools, processes, and complete factories. These analysis, measurement and control products are essential for gas leak detection in air conditioning/refrigeration and automotive manufacturing. They are vital to equipment manufacturers and end-users in the complex fabrication of semiconductors and thin film coatings for optics, flat panel displays, solar cells and industrial vacuum coating applications. Other users of our vacuum-based processes include the life sciences, research, aerospace, packaging, heat treatment, laser cutting and many other industrial processes. We also leverage our expertise in vacuum technology to provide unique, toxic chemical analysis products for emergency response, security, and environmental health and safety.

Job Description

INFICON is seeking a strategic and forward‑thinking Supply Chain Analytics Manager to lead the ISS Division’s supply chain analytics strategy, data architecture, KPI design, reporting, and decision-support capabilities. In this high-impact role, you will transform complex operational data into actionable insight that improves planning accuracy, optimizes inventory and working capital, enhances supplier performance, and drives operational excellence across a global high-tech manufacturing environment.

Partnering closely with cross-functional leaders across planning, procurement, operations, and finance, you will build the visibility, discipline, and predictive capability needed to support faster, smarter decisions across the end-to-end supply chain. This is an opportunity to make a visible impact within an innovation-led organization where analytics is a critical driver of growth, efficiency, and customer success.

Key Responsibilities:
 

• Lead the ISS Division’s end-to-end supply chain analytics strategy, including KPI architecture, reporting governance, and performance measurement across planning, procurement, inventory, and logistics.
• Develop and maintain executive-ready dashboards and reporting that provide visibility into on-time delivery, material availability, inventory turns, forecast accuracy, supplier performance, and procurement cost trends.
• Serve as the analytical lead for the monthly SIOP process, supporting demand planning, consensus forecasting, supply-demand balancing, risk assessment, and leadership decision-making.
• Build models and decision-support tools to evaluate forecast accuracy, revenue at risk, supply constraints, capacity exposure, and scenario outcomes.
• Deliver procurement and supplier analytics, including spend analysis, PPV tracking, lead-time performance, supplier scorecards, and cost-reduction measurement to support sourcing and QBRs.
• Build and manage data pipelines and reporting structures from SAP (MM, PP, SD, WM) and related systems, enabling scalable, automated analytics and self-service reporting through Power BI, Tableau, or SAP Analytics Cloud.
• Establish and enforce data governance standards to ensure accuracy, consistency, and integrity across supply chain data sources.
• Identify operational inefficiencies and drive cross-functional continuous improvement initiatives through predictive analytics, leading indicators, and digital supply chain tools.

Qualifications

Education

• Bachelor’s degree in Supply Chain, Industrial Engineering, Data Science, Operations Research, Business Analytics, or related quantitative field.

Required Experience

• 7+ years of experience in supply chain analytics, operations analytics, or business intelligence within complex manufacturing environments.
• Proven success building KPI frameworks, data models, and analytics tools in multi‑product, global supply chain settings.
• Strong experience using an ERP as an analytics tool 
• Advanced proficiency in data visualization (Power BI or Tableau), including data modeling and executive dashboard design.
• Strong SQL and data transformation skills.  
• Familiarity with forecasting methods, SIOP/S&OP analytics, capacity modeling, and inventory optimization.
• Advanced Excel capability for analytical modeling and automation.

Preferred Experience / Qualifications:

• Experience in semiconductor equipment, precision instruments, medical devices, aerospace/defense, or industrial technology.
• Strong SAP expertise across PP, MM, SD, and WM; capable of interpreting MRP logic and ERP data structures is highly desired 
• Experience with Python or R.
• Master’s degree (MBA, MS in Supply Chain, Data Science, or Engineering).
• Certific