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Amazon
Are you passionate about applying machine learning and advanced statistical techniques to protect one of the world's largest online marketplaces? Do you want to be at the forefront of developing innovative solutions that improve Amazon's customers experience? Do you thrive in a collaborative environment where diverse perspectives drive breakthrough solutions?
If yes, we invite you to join the Amazon Customer Fulfillment & Prime analytics team. We're seeking an exceptional scientist who can revolutionize how we delight our customers. As a key member of our team, you'll develop and deploy machine learning systems that analyze millions of customer interactions daily, ensuring state of art experience for customers across 10 countries. Your work will directly impact the shopping experience for hundreds of millions of customers worldwide.
Key job responsibilities
• Use machine learning and statistical techniques to create scalable abuse detection solutions that identify fraudulent customer behavior, rings of accounts, identity change, holistic customer risk and marketplace manipulation schemes
• Innovate with the latest GenAI technology to build highly automated solutions for efficient customer promotions
• Design, develop and deploy end-to-end machine learning solutions in the Amazon production environment to delight Amazon customers
• Collaborate with cross-functional teams to develop comprehensive ML/statistical models that can scale to millions of customers and 10+ countries
About the team
You'll be working closely with business partners, science and engineering teams to create end-to-end scalable machine learning solutions that address real-world problems. You will build scalable, efficient, and automated processes for large-scale data analyses, model development, model validation, and model implementation.
You will also be providing clear and compelling reports for your solutions and contributing to the ongoing innovation and knowledge-sharing that are central to the team's success.- 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
- Master's degree in Math, Statistics, Computer Science, or related science field, or Master's degree
- 3+ years of data scientist experience
- 2+ years of machine learning/statistical modeling data analysis tools and techniques, and parameters that affect their performance experience
- Experience applying theoretical models in an applied environment
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