Have you ever wondered how that Amazon box with the smile arrives so quickly, where it came from, and how much it cost Amazon to deliver? The WW Amazon Logistics, Business Analytics team manages the delivery of tens of millions of products every week to Amazon's customers, achieving on-time delivery in a cost-effective manner.
We are seeking an enthusiastic, customer-obsessed Principal Applied Scientist with strong analytical skills to join our team. This role is crucial in optimizing Amazon's vast delivery network and will have significant impact on the customer experience, particularly in the final phase of delivery.
As a Principal Applied Scientist, you will:
1. Address business challenges through building compelling cases and using data to influence change across the organization
2. Develop input and assumptions based on preexisting models to estimate costs and savings opportunities associated with varying levels of network growth and operations
3. Create metrics to measure business performance, identify root causes and trends, and prescribe action plans
4. Manage multiple high-impact projects simultaneously
5. Work with technology teams and product managers to develop new tools and systems supporting business growth
6. Communicate with and support various internal stakeholders and external audiences
7. Implement scheduling solutions, improve metrics, and develop scalable processes and tools
The ideal candidate will have:
- PhD in Operations Research, Statistics, Engineering, or Supply Chain Management
- Extensive experience in operations research and data-driven decision making
- Strong analytical and problem-solving skills
- Robust program management and research science skills
- Ability to work with a team and make independent decisions in ambiguous environments
- Customer-obsessed mindset with a focus on improving the Amazon delivery experience
This role offers the autonomy to think strategically and make data-driven decisions from day one. Join us in shaping the future of e-commerce delivery and addressing the core challenges in our world-class operations space!
Key job responsibilities
1. Advanced Modeling and Algorithm Development:
- Design and implement sophisticated machine learning models for logistics optimization
- Develop complex time series forecasting algorithms for demand prediction and resource allocation
2. AI and Machine Learning Integration:
- Architect and deploy AI-powered systems to enhance decision-making in logistics operations
- Implement deep learning techniques for image recognition in package sorting and handling
- Develop reinforcement learning algorithms for adaptive scheduling and resource management
3. Big Data Analytics and Processing:
- Design and implement distributed computing solutions for processing massive logistics datasets
- Utilize cloud computing platforms (e.g., AWS) for scalable data processing and analysis
5. AI-Driven Workflow Optimization:
- Design and implement AI agents for autonomous decision-making in logistics processes
- Create machine learning models for customer behavior analysis and personalized delivery options
6. Software Development and System Architecture:
- Write efficient, scalable code in languages such as Python, Java, or C++
- Develop and maintain complex software systems for logistics optimization
- Stay at the forefront of AI and ML research
- Publish research findings in top-tier conferences and journals
About the team
We are Amazon's Last Mile Science and Analytics team, dedicated to improving e-commerce delivery. We work to optimize our vast network, forecast demand using machine learning, and enhance route efficiency. Our efforts focus on developing innovative delivery methods, applying AI to solve complex problems, and conducting geospatial analysis. We create simulations to refine processes and plan capacity effectively. Operating globally, we strive to develop adaptable solutions for diverse markets. We aim to advance logistics science, continually improving speed, efficiency, and customer satisfaction, in support of Amazon's mission to be Earth's most customer-centric company.
