Job
Description
Responsibilities: Collaborate effectively with diverse, cross-functional teams to identify improvement opportunities and implement data-driven solutions. Analyze complex supply chain data to develop insights and recommendations for enhancing operational efficiency and reducing costs. Leverage advanced analytics tools, models, and reports to support decision-making, improve visibility, and enhance forecasting accuracy. Conduct statistical analysis to monitor supply chain performance and evaluate key performance indicators (KPIs). Work with the Data Visualization team to create impactful dashboards, ensuring clear communication of performance metrics to stakeholders. Lead continuous improvement initiatives, using data insights to drive process enhancements and monitor effectiveness. Stay informed about emerging trends, technologies, and best practices in supply chain management, applying them to drive innovation. Conduct in-depth analysis of processes like demand forecasting, inventory management, and logistics to identify optimization opportunities. Provide strategic recommendations to senior leadership based on data insights, aiming to improve efficiency and reduce costs. Ensure seamless communication and collaboration with global stakeholders across different time zones. Mentor and guide team members, fostering their professional development in global supply chain management. Translate complex analytics into clear, actionable language for stakeholders at all levels. Develop and deliver core and ad-hoc analyses, supporting decision-making for managers and leaders. Create and maintain business-specific reports, dashboards, and analytical solutions using AI/BI tools, SAP, SQL Server, and other sources. Qualifications & Competencies: Bachelor's or Master's degree in Supply Chain Management, Data Science, Statistics, Business Analytics, or related fields. 10+ years of experience in data analysis, business intelligence, or supply chain analytics, preferably in the automotive industry. Proficiency in Python, advanced Excel, and data visualization tools like Tableau or PowerBI. Experience with data engineering tools like ETL, Azure Data Warehouse, and Azure Databricks. Strong understanding of supply chain management, including inventory, transportation, procurement, and demand forecasting. Expertise in database structures, data modeling, and data management principles. Strong analytical and problem-solving skills, with the ability to turn complex data into actionable insights. Knowledge of SAP in the context of supply chain management is preferred. Excellent communication and presentation skills for both technical and non-technical audiences.
