Amazon aims to exceed the expectations of our customers by ensuring that their orders, no matter how large or small, are delivered as quickly, accurately, and cost effectively as possible. To meet this goal, Amazon has invested in Amazon Logistics, a world class last mile operation. We are looking for a dynamic, resourceful, and organized Scientist within Amazon Logistics' Amazon Flex organization to develop new, data-driven solutions to support the most critical components of this rapidly scaling operation.
As part of the Last Mile Science & Technology organization, you'll partner closely with Product, Tech, and Program teams to design innovative solutions to organizational and business problems, using machine learning best practices. You will develop new sophisticated algorithms and improve existing approaches based on machine learning algorithms and big data solutions. You will be expected to be a subject matter expert in machine learning science and to communicate highly complex findings to multiple audiences.
In addition to designing meaningful research questions and analyzing the resulting data, you must be able to see a full loop vision that goes beyond experimentation and proof of concept to conceptualizing design solutions, collaborating closely with multiple teams to ensure the relevance and impact of your work to business stakeholders. You will be expected to be a thought leader as we chart new courses with our delivery support technologies.
• Execute global research initiatives
• Conduct, direct, and coordinate all phases of research projects, demonstrating skill in all stages of the analysis process, including defining key research questions, recommending measures, working with multiple data sources, evaluating methodology and design, executing analysis plans, interpreting and communicating results
• Share deep knowledge in machine learning to our problem space.
• Work in an ambiguous environment
• PhD or Master's degree in Machine Learning, Computer Science, Computer Engineering, Statistics, Applied Mathematics, or a related field
• Experience building machine learning models
• Fluency in a high-level modeling language such as Python or other statistical software
• Strong communication, influencing and partnership skills
• A natural curiosity and desire to learn
• Ability to convey rigorous mathematical concepts and considerations to non-experts
• Ability to distill problem definitions, models, and constraints from informal business requirements
• Ability to deal with ambiguity and competing objectives
• Experience with big data and analytics
• Experience designing and supporting large-scale distributed systems in a production environment
• Knowledge of machine learning applications in predictive and prescriptive modeling, personalization, recommendation, pricing, fraud detection and prevention.