Do you aspire to become a Data Scientist, ML Engineer, Applied Scientist or Research Scientist at Amazon? This guide will provide you comprehensive details about the interview process and preparation tips to help you ace the data interviews at Amazon. I created dataInterview.com to help a candidate such as yourself ace data science interviews and land your dream role at a top company. Make sure to check it out! Before we start, please note that that the exact interview experience at Amazon can vary given the role, team, and interviewer's preference. In general, the details and tips provided should be helpful with your interview prep. As you might already know, Amazon is a conglomerate of multiple businesses from e-commerce (Amazon.com),

The Amazon ML interview, called the Machine Learning Engineer Interview, focuses heavily on e-commerce ML tools, cloud computing, and AI recommendation systems. Amazon ML engineers are expected to build ML systems and use Deep Learning models. Research scientists have higher levels of education and work to improve ASR, NLU, and TTS features. The technical portion of the ML interview focuses on ML models, bias-variance tradeoff, and overfitting. The Facebook ML Interview consists of generic algorithm questions, ML design, and system design.

IBM is a multinational technology company founded in 1911 and operates in over 170 countries worldwide. Today, IBM offers a wide spectrum of products and services that includes software solutions, hardware architecture (server and storage architecture), business and technology services, and global financing solutions. As a data driven-company, IBM understands the importance of data and data analytics at every layer of organization to drive better business decisions. Also, a leading provider of Analytics and Cloud-based solutions, IBM offers a full stack of cloud-based products and services spanning across data analytics, storage, AI, IoT, and blockchain. Check out this article about the Microsoft Data Scientist interview!