Analyst, Plan Optimization, EU AMZL Network Process Optimization

Amazon - Milan, MI

Full-time - Entry Level

Milan, MI

Sporting Goods, Hobby, Musical Instrument, Book, and Miscellaneous Retailers

About the position

The Plan Optimization Analyst role at Amazon focuses on enhancing the last-mile logistics operations by leveraging optimization and machine learning techniques. This position involves collaborating with software engineers, product managers, and business teams to identify challenges and develop actionable solutions that improve the fulfillment pipeline. The analyst will lead analyses, communicate findings to leadership, and drive operational improvements while managing various responsibilities in a dynamic environment.

Responsibilities

• Solve complex optimization and machine learning problems using scalable algorithmic techniques.
• Design and develop efficient research prototypes that address real-world problems in the last-mile operations of Amazon.
• Lead complex time-bound, long-term as well as ad-hoc analyses to assist decision making.
• Communicate to leadership results from business analysis, strategies and tactics.

Requirements

• Bachelor's degree, or equivalent.
• Experience in deep diving operational metrics and problem solving.
• Experience with some programming language (Java/python/C++).
• Experience leading and interacting with cross-functional teams.
• Proficient with Microsoft Excel.
• Fluent in written and spoken English.

Nice-to-haves

• Master's degree, or equivalent.
• Academic or work experience on Optimization Research.
• Presentation skills.
• Good organization skills and ability to organize and manage multiple tasks simultaneously.
• Good oral and written communication skills, as well as ability to think clearly, analyze quantitatively and problem-solve.
• Business judgment, ability to influence others, and good analytical thinking skills.
• Ability to evaluate priorities appropriately, apt at resolving conflict and to communicate intentions clearly, delivering within time constraints.