Supply Chain Data Analyst
- High exposure to senior leadership; this is flat hierarchy, and your ideas will be heard.
- Opportunity to work on growth projects that will help define the future of Trivium Packaging.
- Commitment to your professional development.
- Competitive compensation and benefits.
- High-performance culture with impressive and experienced colleagues.
- Data Collection, Validation & Wrangling - Collect, clean, transform, and validate manufacturing and supply chain data from systems such as Sage 300, Siemens Preactor, MES, and Forecast X. Collaborate with frontline staff to ensure data integrity and gather insights from the shop floor.
- Advanced Analytics & AI Enablement - Apply statistical and AI/ML techniques (e.g., regression, clustering, anomaly detection, forecasting) to analyze production metrics, inventory cycles, labor variances, and quality data. Generate actionable insights to support decision-making and planning agility.
- Reporting & Visualization - Develop and maintain dashboards and visual reports for SIOP, inventory, production, and credit utilization using BI tools (e.g., Power BI, Tableau). Communicate key performance indicators and improvement progress clearly to stakeholders.
- Continuous Improvement & Process Optimization - Participate in and support continuous improvement initiatives by identifying areas for optimization through data-driven analysis. Collaborate with manufacturing teams to implement and monitor the impact of solutions.
- System Integration & Modernization Support - Assist in the configuration and testing of MRP and APS features. Collaborate with IT and external partners to support system integrations and ensure reliable data flows across platforms.
- Business Process Documentation & Enablement - Document workflows and business processes related to modernization projects. Maintain a centralized knowledge base of updated procedures, system changes, and reference materials.
- User Acceptance Testing (UAT) & Change Management - Develop cases and test scenarios for new system features. Coordinate UAT cycles, track defects, and gather stakeholder feedback. Support change management activities including training, communication planning, and adoption tracking.
- Training & Stakeholder Engagement - Create and deliver training materials and quick reference guides tailored to planners, analysts, and cross-functional teams. Engage with stakeholders to ensure successful adoption of new tools and processes.
- Hands-On Operational Engagement - Spend time on the manufacturing floor to understand operational challenges and opportunities. Work closely with production teams to ensure practical alignment of analytics with real-world processes.
- Strong foundation in statistical analysis and a demonstrated ability to apply statistical and AI/ML methods (e.g., regression, clustering, forecasting) to real-world supply chain and manufacturing challenges.
- Proficiency in data tools including Microsoft Excel, SQL, Power BI, and Tableau; experience with Python or R is a plus.
- Experience with ERP systems (preferably Sage 300), APS tools (e.g., Siemens Preactor), and MES platforms.
- Skilled in data extraction, transformation, and visualization to support decision-making and continuous improvement.
- Excellent ability to present complex analyses clearly and persuasively to senior leadership and cross-functional teams.
- Strong documentation and business process mapping skills; experience supporting UAT and system testing cycles.
- Highly organized, detail-oriented, and capable of managing projects independently with a high degree of accuracy and precision.
- Strong verbal and written communication skills with a collaborative, hands-on, and proactive approach.
- Growth mindset with a willingness to learn by doing and contribute in a dynamic manufacturing environment.
- Bachelor’s degree in supply chain, Data Science, Industrial Engineering, or a related field.
- Minimum 3 years of experience in supply chain analytics, business analysis, or manufacturing operations.
- Exposure to change management frameworks (e.g., ADKAR, Prosci) is a plus.
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