Data Scientist II, International Seller Services

At Amazon, we strive to be Earth's most customer-centric company, where customers can find and discover anything they want to buy online. Our mission in International Seller Services (ISS) is to provide technology solutions for improving the seller and customer experience, drive seller compliance, maximize seller success, and improve internal workforce productivity. Team's main focus is to build products that are scalable across different regions of the world, while working in partnership with ISS regional stakeholders and multiple partner teams across Amazon.

As a Data Scientist, you will be responsible for modeling complex problems, discovering insights, and building risk algorithms that identify opportunities through statistical models, machine learning, and visualization techniques to improve operational efficiency.

As a Data Scientist, you will leverage your expertise in Machine Learning, Natural Language Processing (NLP), and Large Language Models (LLM) to develop innovative solutions for Amazon's ISS team. You'll be responsible for modeling complex problems, building innovative algorithms, and discovering actionable insights through statistical models and visualization techniques to enhance operational efficiency in the e-commerce space. The role combines usage of latest AI technology with practical business applications, requiring someone passionate about transforming the way we interact with technology while delivering measurable impact through advanced analytics and machine learning solutions.

You will need to collaborate effectively with business and product leaders within ISS and cross-functional teams to build scalable solutions against high organizational standards. The candidate should be able to apply a breadth of tools, data sources, and Data Science techniques to answer a wide range of high-impact business questions and proactively present new insights in concise and effective manner. The candidate should be an effective communicator capable of independently driving issues to resolution and communicating insights to non-technical audiences. This is a high impact role with goals that directly impacts the bottom line of the business.

Key job responsibilities Analyze terabytes of data to define and deliver on complex analytical deep dives to unlock insights and build scalable solutions through Data Science to ensure security of Amazon’s platform and transactions

Build Machine Learning and/or statistical models that evaluate the transaction legitimacy and track impact over time Ensure data quality throughout all stages of acquisition and processing, including data sourcing/collection, ground truth generation, normalization, transformation, and cross-lingual alignment/mapping Define and conduct experiments to validate/reject hypotheses, and communicate insights and recommendations to Product and Tech teams Develop efficient data querying infrastructure for both offline and online use cases Collaborate with cross-functional teams from multidisciplinary science, engineering and business backgrounds to enhance current automation processes Learn and understand a broad range of Amazon’s data resources and know when, how, and which to use and which not to use. Maintain technical document and communicate results to diverse audiences with effective writing, visualizations, and presentations

Basic Qualifications: - 2+ years of data scientist 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 machine learning/statistical modeling data analysis tools and techniques, and parameters that affect their performance experience - 1+ years of guiding and coaching a group of researchers experience - 1+ years of working with or evaluating AI systems experience - 1+ years of creating or contributing to mathematical textbooks, research papers, or educational content experience - Master's degree in Science, Technology, Engineering, or Mathematics (STEM), or experience working in Science, Technology, Engineering, or Mathematics (STEM) - Experience applying theoretical models in an applied environment

Preferred Qualifications: - Ph.D. in Science, Technology, Engineering, or Mathematics (STEM) - Knowledge of machine learning concepts and their application to reasoning and problem-solving - Experience in Python, Perl, or another scripting language - Experience in a ML or data scientist role with a large technology company - Experience in defining and creating benchmarks for assessing GenAI model performance - Experience working on multi-team, cross-disciplinary projects - Experience applying quantitative analysis to solve business problems and making data-driven business decisions - Experience effectively communicating complex concepts through written and verbal communication

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