Supply Chain Data & Forecasting Analyst

Responsibilities

• developing data-driven insights to support demand forecasting, procurement planning, and production scheduling within a manufacturing environment
• analyzing data, building models, and identifying risks and opportunities across the supply chain
• analyzing forecast performance
• providing insights to improve forecast reliability and reduce bias
• analyzing procurement data from ERP systems to align purchasing with forecasted demand
• monitoring supplier performance with supplier scorecards including lead times, on-time delivery, variability and reliability, and quality
• evaluating inventory levels against forecast and open purchase orders
• working with Finance to perform cost and spend analysis to support procurement decisions
• identifying gaps between demand, supply, and capacity
• ensuring product progression throughout ERP Integrated Supply Chain Analysis
• connecting and analyzing forecasting, inventory, procurement, and production
• providing insights on trade-offs between service levels, inventory investment, and production efficiency
• supporting S&OP process with data-driven analysis and reporting
• extracting and analyzing data from Accoountmate and Alere
• providing data-driven recommendations and scenario analysis
• identifying risks, opportunities, and optimization strategies
• clearly communicating trade-offs and impacts
• using Excel/Power BI for modeling and analysis: data cleaning, forecast modeling, automation and scenario analysis to build dashboards and visualizations, and automate reporting processes to improve visibility and decision speed

• Bachelor’s degree in Supply Chain, Operations, Business, Engineering, or related field
• 0-5 years’ experience in a manufacturing setting or equivalent
• Experience analyzing large datasets required
• Advanced proficiency in Microsoft Excel (pivot tables, lookups, data modeling)
• Experience with ERP/MRP systems (SAP, Oracle, Net Suite, etc.)
• Experience with Power BI, Tableau, or similar tools preferred
• Strong analytical mindset with a focus on cost, performance, and data integrity
• High accountability with a results-driven approach
• Strong quantitative and problem-solving abilities
• Ability to analyze complex datasets across multiple platforms
• Strong attention to detail and accuracy
• Quality and timeliness of analytical insights
• Ability to translate data into clear, actionable insights
• Strong collaboration and communication skills
• Continuous improvement mindset aligned to operational excellence.