Develop and implement supply chain models using Python, R, or other advanced tools to optimize end-to-end processes, including planning, network design, inventory management, and distribution.
Build advanced analytics, statistical models, and forecasting tools to predict and optimize parcel costs and delivery timelines.
Leverage data to analyze and enhance delivery speed performance, focusing on streamlining last-mile logistics.
Evaluate and benchmark carrier performance using key metrics like cost per package and delivery speed.
Collaborate with last-mile logistics teams to optimize delivery routes and improve efficiency.
Work with supply chain leadership, data engineers, and IT teams to ensure data integrity and system integration, supporting cross-functional teams with data-driven insights for decision-making.
Continuously explore emerging technologies and methodologies to adopt best practices and enhance supply chain operations.
Requirements
Education: Bachelor's or Master's degree in Supply Chain Management, Data Science, Computer Science, or a related field.
5+ years of experience in supply chain analytics, business analysis, or a related field, with a focus on data science and optimization.
Proven experience with data analysis, statistical modeling, and machine learning techniques in a supply chain context.
Proficiency in programming languages such as Python and R for data analysis, modeling, and automation. Strong knowledge of data visualization tools (e.g., Tableau, Power BI) and experience in creating interactive dashboards and reports.
Strong quantitative and analytical skills, with the ability to turn complex data into clear insights and actionable recommendations. Ability to solve complex supply chain problems using data-driven approaches and optimization techniques.
Excellent verbal and written communication skills, with the ability to communicate complex data findings and technical details to non-technical stakeholders.
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