Supply Chain Analyst – Analytics & Transformation

Work Schedule Standard (Mon-Fri) Environmental Conditions Office Job Description Supply Chain Analyst – Analytics & Transformation The Opportunity We are seeking a Supply Chain Analyst to join the Filtration and Separation Division and play a key role in strengthening our supply chain analytics capabilities while supporting a significant ERP transformation. This is an opportunity for someone who enjoys working at the intersection of supply chain, manufacturing, data, technology, and continuous improvement. You will turn complex operational data into actionable insights, develop scalable analytics and automation solutions, and partner across the organization to solve meaningful business challenges. A near-term priority for this role will be supporting the E1 implementation, particularly across Quote-to-Cash (QTC), manufacturing, inventory, and related supply chain processes. You will help ensure critical business data is accurate, complete, and implementation-ready while providing the analytics needed to support a successful transition and minimize disruption. Beyond the implementation, you will help build stronger and more sustainable supply chain capabilities—improving visibility, reducing manual work, identifying systemic issues, and enabling better decisions across inventory, forecasting, fulfillment, customer service, and manufacturing. What You’ll Do Support a Critical ERP Transformation Serve as a key supply chain analytics partner for the E1 implementation, with a focus on QTC and manufacturing requirements. Extract and analyze customer, material, order, inventory, manufacturing, and transactional data from existing ERP and business systems. Cleanse, validate, transform, and reconcile complex datasets to ensure data is accurate, complete, consistent, and ready for implementation. Partner with Supply Chain, Manufacturing, IT, Commercial, Finance, and implementation teams to identify data gaps, resolve issues, and reduce implementation risk. Develop repeatable validation controls and reconciliation processes to support data conversion and business continuity. Provide analytical support during cutover, stabilization, and post-implementation issue resolution. Build reporting that provides clear visibility into implementation readiness, data quality, operational risks, and business performance. Build Better Analytics, Automation & Processes Translate supply chain challenges and business requirements into practical data, reporting, automation, and process solutions. Develop dashboards, analytical tools, and automated workflows that make complex information easier to understand and act upon. Use Python, SQL, Power BI, Excel, automation, and emerging AI-enabled tools to improve the speed, quality, and scalability of supply chain analytics. Identify opportunities to replace manual or spreadsheet-intensive processes with sustainable, repeatable solutions. Investigate systemic data and process issues, identify root causes, and partner with stakeholders to implement lasting improvements. Develop business cases that quantify the operational and financial impact of improvement opportunities. Create standard work, process documentation, and training materials that enable successful adoption of new capabilities. Lead analytical and transformation projects from problem definition through implementation and measurable results. Improve Supply Chain Performance Develop reporting and analytics that improve end-to-end visibility and enable faster, more informed decision-making. Identify trends, constraints, risks, and root causes across supply chain and manufacturing performance and translate them into actionable recommendations. Support initiatives focused on inventory optimization and working capital, back-order reduction, fulfillment and customer service improvement, lead-time reduction, forecast accuracy, and manufacturing and operational performance. Establish meaningful KPIs and performance monitoring that enable teams to proactively identify risks and opportunities. Partner with planning and operational teams to continuously improve forecast accuracy across portfolio, product-family, and key-item levels. How You’ll Get Here Education: Bachelor’s degree in Supply Chain, Data Science, Engineering, Business Analytics, or a related field required. Experience & Qualifications: 4&#43; years of experience working with end-to-end supply chain processes such as planning, inventory management, manufacturing, order fulfillment, or customer service. Experience extracting, transforming, validating, and analyzing data from ERP and other enterprise business systems. Hands-on experience using Python for data transformation, validation, automation, or analytics. Strong working knowledge of SQL, including querying, joining, validating, and analyzing data across multiple sources. Experience developing Power BI dashboards, data models, KPIs, and business performance reporting. Demonstrated ability to work with large, complex datasets and translate analysis into clear business insights and recommendations. Experience supporting ERP implementations, system transformations, process improvements, or significant changes to reporting and analytics capabilities. Strong analytical and problem-solving skills with the ability to move from symptoms to root causes and practical solutions. Ability to translate business needs into data, system, reporting, and process requirements. Experience partnering across functions such as Supply Chain, Manufacturing, IT, Finance, Commercial, and Operations. Ability to manage multiple priorities, stakeholders, risks, and deliverables in a dynamic environment. Skills That Will Help You Stand Out You do not need to have experience with everything below. We are especially interested in candidates who bring a strong analytical foundation, curiosity, and an interest in using technology to solve supply chain problems. Advanced Microsoft Excel and data-modeling capabilities. Experience using scripting and automation to eliminate manual processes and improve data quality and reporting efficiency. Experience with ETL, data transformation, data integration, data governance, master data, or data-validation methodologies. Experience developing repeatable data pipelines, automated controls, or scalable analytical solutions. Familiarity with ERP migration, data conversion, system transformation, and reconciliation activities. Experience integrating data across multiple enterprise systems. Experience using AI-enabled development or analytics tools, such as Codex or similar AI coding assistants, to accelerate analysis, automation, documentation, or solution development. Interest in applying AI and advanced analytics to supply chain challenges such as exception management, forecasting, inventory optimization, data quality, and root-cause analysis. What Will Make You Successful </