Applied Scientist, International Machine Learning

About the Role

Do you want to join an innovative team of scientists who use machine learning and statistical techniques to create state-of-the-art solutions for providing better value to Amazon’s customers? Do you want to build and deploy advanced algorithmic systems that help optimize millions of transactions every day? Are you excited by the prospect of analyzing and modeling terabytes of data to solve real world problems? Do you like to own end-to-end business problems/metrics and directly impact the profitability of the company? Do you like to innovate and simplify? If yes, then you may be a great fit to join the Machine Learning and Data Sciences team for India Consumer Businesses.

If you have an entrepreneurial spirit, know how to deliver, love to work with data, are deeply technical, highly innovative and long for the opportunity to build solutions to challenging problems that directly impact the company's bottom-line, we want to talk to you.

Major Responsibilities

• Use machine learning and analytical techniques to create scalable solutions for business problems
• Analyze and extract relevant information from large amounts of Amazon’s historical business data to help automate and optimize key processes
• Design, development, evaluate and deploy innovative and highly scalable models for predictive learning
• Research and implement novel machine learning and statistical approaches
• Work closely with software engineering teams to drive real-time model implementations and new feature creations
• Work closely with business owners and operations staff to optimize various business operations
• Establish scalable, efficient, automated processes for large scale data analyses, model development, model validation and model implementation
• Mentor other scientists and engineers in the use of ML techniques

Basic Qualifications

• Experience programming in Java, C++, Python or related language
• Experience with SQL and an RDBMS (e.g., Oracle) or Data Warehouse

Preferred Qualifications

• Experience implementing algorithms using both toolkits and self-developed code
• Have publications at top-tier peer-reviewed conferences or journals