Data Scientist, Amazon

• 3+ years of machine learning, statistical modeling, data mining, and analytics techniques experience
• 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
• 3+ years of data scientist or similar role involving data extraction, analysis, statistical modeling and communication experience
• Experience applying theoretical models in an applied environment

Desirable

• Are you looking for an environment where you can drive innovation, apply state-of-the-art machine learning techniques, and tackle real-world problems at massive scale? Do you want to shape the future of Amazon’s Retail business by designing and deploying deep learning models for time series forecasting? If so, join the Amazon Demand Forecasting Science team!
• 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