Applied Scientist, Modeling and Optimization (MOP)

Do you enjoy solving challenging problems and driving innovations in research? Are you seeking for an environment with a group of motivated and talented scientists like yourself? Do you want to create scalable optimization models and apply machine learning techniques to guide real-world decisions? Do you want to play a key role in the future of Amazon transportation and operations? Come and join us at Amazon's Modeling and Optimization team (MOP).

Key job responsibilities
An Applied Scientist in the Modeling and Optimization (MOP) team
- provides analytical decision support to Amazon planning teams via applying advanced mathematical and statistical techniques.
- collaborates effectively with Amazon internal business customers, and is their trusted partner
- is proactive and autonomous in discovering and resolving business pain-points within a given scope
- is able to identify a suitable level of sophistication in resolving the different business needs
- is confident in leveraging existing solutions to new problems where appropriate and is independent in designing and implementing new solutions where needed
- is aware of the limitations of their proposed solutions and is proactive in communicating them to the business, and advances the application of sciences towards Amazon business problems by bringing new methods, ideas, and practices to the team and scientific community.

A day in the life
- Your will be developing model-based optimization, simulation, and/or predictive tools to identify and evaluate opportunities to improve customer experience, network speed, cost, and efficiency of capital investment.
- You will quantify the improvements resulting from the application of these tools and you will evaluate the trade-offs between potentially competing objectives.
- You will develop good communication skills and ability to speak at a level appropriate for the audience, will collaborate effectively with fellow scientists, software development engineers, and product managers, and will deliver business value in a close partnership with many stakeholders from operations, finance, IT, and business leadership.

About the team
- At the Modeling and Optimization (MOP) team, we use mathematical optimization, algorithm design, statistics, and machine learning to improve decision-making capabilities across WW Operations and Amazon Logistics.
- We focus on transportation topology, labor and resource planning for fulfillment facilities, routing science, visualization research, data science and development, and process optimization.
- We create models to simulate, optimize, and control the fulfillment network with the objective of reducing cost while improving speed and reliability.
- We support multiple business lanes, therefore maintain a comprehensive and objective view, coordinating solutions across organizational lines where possible.