Data Scientist, Amazon

• 3+ years of data querying languages (e.g. SQL), scripting languages (e.g. Python) or statistical/mathematical software (e.g. R, SAS, Matlab, etc.) experience
• 2+ years of data scientist experience
• 3+ years of machine learning/statistical modeling data analysis tools and techniques, and parameters that affect their performance experience
• Bachelor's degree
• Experience applying theoretical models in an applied environment

Desirable

• As part of this dynamic team, you will create and implement novel neural network architectures to develop the next generation of foundation time series models, directly influencing how Amazon operates at a global scale
• Design new deep learning algorithms and creative approaches to push time series forecasting performance beyond the current state-of-the-art
• Work cross-functionally with product managers, software engineers, and scientists to build end-to-end solutions that are deployed at scale in Amazon’s production systems
• Engage with the broader scientific community at Amazon and beyond - collaborate with academic researchers, contribute to publications, and present your work at leading conferences (e.g., NeurIPS)
• You will deep dive into massive Amazon time series datasets, leveraging Python and PySpark to conduct exploratory data analysis
• You will prep the data pipeline - writing Python code to train, evaluate, and debug the latest deep learning models
• You will design novel neural network architectures, brainstorming with fellow scientists and engineers on ways to push the boundaries of foundation time series modeling
• You may explore and benchmark open-source solutions, identifying opportunities to enhance Amazon’s forecasting capabilities
• You will document your discoveries and prepare them for internal knowledge-sharing sessions or external conferences, ensuring that your innovations help shape the future of demand forecasting - both within Amazon and the broader research community