About the job
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).
Responsibilities
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.
Qualifications
Minimum
PhD, or Master's degree and 4+ years of quantitative field research experience
Experience investigating the feasibility of applying scientific principles and concepts to business problems and products
Experience analyzing both experimental and observational data sets
Preferred
Knowledge of R, MATLAB, Python or similar scripting language
Experience with agile development
Experience building web based dashboards using common frameworks