Job Description

Role & responsibilities We are seeking a Business Analyst with an extensive background in supply chain, preferably in the Automotive sector. The ideal candidate must have a strong background in analyzing and optimizing supply chain processes using data-driven insights. Responsibilities include gathering and analyzing supply chain data, identifying areas for improvement which would result in enhancing efficiency and reduce costs. Responsibilities : Foster effective collaboration with diverse teams across various functions and regions. Collect and analyze large datasets to identify patterns, trends, and insights that will inform business strategies and decision-making processes. Develop and maintain reports, dashboards, and other tools to monitor and track supply chain performance. Assist in the development and implementation of supply chain strategies that align with business objectives. Identify and suggest solutions to potential supply chain risks and challenges. Build data models and perform data mining to discover new opportunities and areas of improvement. Conduct data quality checks to ensure accuracy, completeness, and consistency of data sets. Develop predictive and prescriptive data models to support forecasting and optimization efforts. Preferred candidate profile Requirements: Bachelors or master’s degree in supply chain management, Data Science, Statistics, Mathematics, business analytics, or a related field. Minimum 5+ years’ work experience in related role. Proven experience in data analysis, business intelligence, or supply chain analytics, preferably in the automotive industry. Proficiency in statistical analysis tools like Python, Advance excel, as well as data visualization tools such as Tableau or Power BI. Knowledge on Data Engineering tools like ETL, Azure DW, Azure Databricks. Strong knowledge of supply chain management concepts, including inventory management, transportation, procurement, and demand forecasting. Solid understanding of database structures, data modeling, and data management principles. Perks and benefits