Manager Freight Analyst

As a highly analytical and detail-oriented Freight Analyst, your role is to optimize logistics and freight operations by leveraging data analytics, Excel, Power BI, Tableau, and machine learning. Your responsibilities include maintaining and circulating comprehensive Freight Management Information System (MIS) reports, managing a centralized repository of all freight-related data, and identifying key insights through data analysis to drive process improvements and cost optimization. Key Responsibilities: - Analyze freight costs, route efficiency, carrier performance, and shipment trends to optimize logistics operations. - Develop predictive models using machine learning to forecast freight costs and demand fluctuations. - Monitor freight rates, tariffs, and fuel costs to identify cost-saving opportunities. - Optimize lane selection, route planning, and shipment scheduling based on data insights. - Use Excel, Power BI, and Tableau to create dashboards and reports for freight performance tracking. - Manage and analyze large datasets related to transportation, warehousing, and supplier logistics. - Implement data-driven decision-making to improve freight and supply chain efficiency. - Work closely with logistics teams, carriers, and warehouse managers to streamline operations. - Provide insights to procurement, supply chain, and finance teams for cost-effective shipping strategies. - Identify inefficiencies in the supply chain and recommend process automation. - Implement AI-driven predictive analytics to enhance freight planning. - Utilize machine learning models for route optimization and demand forecasting. - Develop tools and algorithms to improve freight cost modeling and risk assessment. Qualification Required: - Bachelor's degree with 5+ years of experience in Logistics, Supply Chain, Data Science, Business Analytics, or a related field. - Advanced Excel skills (Pivot Tables, Macros, Power Query). - Expertise in Power BI, Tableau, and other data visualization tools. - Experience with SQL, Python, or R for data analysis is a plus. - Strong knowledge of transportation management systems (TMS) and freight cost structures. - Understanding of machine learning concepts and their application in logistics. - Excellent problem-solving skills and ability to interpret complex data.,