Find & Apply For Logistics / Supply Chain Analyst Jobs In Rockingham, New Hampshire

Logistics / Supply Chain Analyst jobs in Rockingham, New Hampshire involve analyzing and optimizing supply chain processes to ensure efficient operations. Responsibilities include data analysis, identifying cost-saving opportunities, and collaborating with various departments to streamline logistics. Strong analytical skills and attention to detail are essential for success in this role. Below you can find different Logistics / Supply Chain Analyst positions in Rockingham, New Hampshire.

Latest Jobs in Rockingham

Salary Information & Job Trends In this Region

Logistics / Supply Chain Analysts in Rockingham, New Hampshire play a crucial role in managing and optimizing the flow of goods and services in the supply chain. - Entry-level Logistics Analyst salaries range from $45,000 to $55,000 per year - Mid-career Supply Chain Analyst salaries range from $55,000 to $70,000 per year - Senior-level Logistics Manager salaries range from $70,000 to $90,000 per year The history of Logistics / Supply Chain Analysts in Rockingham, New Hampshire can be traced back to the industrial revolution, where the need for efficient transportation and distribution of goods became apparent. Over time, with the advancements in technology and globalization, the role of analysts has become more complex and data-driven. The evolution of Logistics / Supply Chain Analysts in Rockingham, New Hampshire has seen a shift towards automation and digitization of processes. With the use of advanced analytics and software tools, analysts are now able to make more informed decisions and streamline operations for improved efficiency. Current trends in Logistics / Supply Chain Analyst roles in Rockingham, New Hampshire include a focus on sustainability and environmental responsibility. Analysts are also adapting to the growing e-commerce market by implementing innovative solutions for last-mile delivery and inventory management. Additionally, the use of artificial intelligence and machine learning is becoming more prevalent in forecasting and demand planning processes.

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