Amazon Devices Reverse Supply Chain delivers world-class supply planning services and accurate forecast guidance to support a seamless customer experience, sustainability and maximum asset recovery for Amazon Devices. We are responsible for guiding millions of returned products through the reverse supply chain.
We're seeking a data scientist who blends advanced machine learning expertise with a genuine passion for product and data-driven innovation. You'll develop sophisticated ML models to revolutionize product development and design for serviceability. Your work will transform customer experiences through scientific methods, deep learning architectures, and state-of-the-art AI models. Success in this position demands exceptional scientific leadership, strong customer focus, software engineering excellence, product vision, and sharp business acumen. You have experience in developing experimental and analytical plans for data modeling processes, use of strong baselines, ability to accurately determine cause and effect relations. You are exceptionally curious to learn and an expert in diving into data to discover hidden patterns and of conducting error/deviation analysis.
Key job responsibilities
1. Develop and drive the data science strategy for Amazon Devices Reverse Supply Chain, aligning it with the Devices and Services vision and overall business goals.
2. Identify high-impact opportunities within the organization and lead the ideation, planning, and execution of data science initiatives to address them.
3. Solve real-world problems by getting and analyzing large amounts of data, diving deep to identify business insights and opportunities, design simulations and experiments, developing statistical and ML models by tailoring to business needs, and collaborating with Scientists, Engineers, BIEs, and Product Managers.
4. Write code (Python, R, Scala, SQL, etc.) to obtain, manipulate, and analyze data
5. Apply statistical and machine learning knowledge to specific business problems and data.
6. Build Machine Learning Pipeline orchestration with AWS (SageMaker, Batch, Lambda, Step Functions)
7. Conduct written and verbal presentations to share insights to audiences of varying levels of technical sophistication.
