Applied Scientist

About the Role

Join an innovative team of scientists utilizing machine learning and statistical techniques to develop cutting-edge solutions that enhance value for Amazon's customers. You will build and deploy advanced algorithmic systems to optimize millions of daily transactions, analyze terabytes of data to solve real-world problems, and directly impact company profitability by owning end-to-end business metrics. If you possess an entrepreneurial spirit, a knack for delivery, a passion for data, a deep technical understanding, and a desire to innovate and simplify, this role is for you. We are seeking individuals eager to build impactful solutions for challenging problems.

Key Responsibilities

• Apply machine learning and analytical techniques to engineer scalable solutions for complex business challenges.
• Analyze and extract critical information from extensive historical Amazon business data to automate and optimize core processes.
• Design, develop, assess, and deploy innovative and highly scalable predictive learning models.
• Research and implement novel machine learning and statistical methodologies.
• Collaborate with software engineering teams to facilitate real-time model deployment and the creation of new features.
• Partner with business stakeholders and operations teams to enhance various business operations.
• Establish efficient, scalable, and automated processes for large-scale data analysis, model development, validation, and implementation.
• Mentor fellow scientists and engineers in the application of machine learning techniques.

A Day in the Life

Your work will involve solving practical problems by acquiring and analyzing substantial datasets, generating actionable insights and identifying opportunities, designing simulations and experiments, and developing robust statistical and machine learning models. The team's efforts are guided by business imperatives, necessitating close collaboration with fellow Scientists, Engineers, and Product Managers across the International Emerging Stores organization. You will be responsible for preparing and presenting findings to diverse audiences, ranging from technical experts to less specialized groups.

About the Team

The Central Machine Learning team works in close partnership with the IES business and engineering units to create impactful machine learning solutions for Emerging Marketplaces. This is an exceptional opportunity to leverage your expertise in machine learning and data mining to directly influence the experience of millions of consumers and end-users.

Basic Qualifications

• A minimum of 3 years of experience in developing models for business applications.
• A PhD, or a Master's degree with 4+ years of experience in Computer Science, Computer Engineering, Machine Learning, or a related field.
• Demonstrated experience through patents or publications in top-tier peer-reviewed conferences or journals.
• Proficiency in programming languages such as Java, C++, Python, or similar.
• Experience in at least one of the following areas: algorithms and data structures, parsing, numerical optimization, data mining, parallel and distributed computing, or high-performance computing.

Preferred Qualifications

• Experience with data applications leveraging large-scale distributed systems (e.g., EMR, Spark, Elasticsearch, Hadoop, Pig, and Hive).
• Proficiency in two or more of the following areas: large language models, Natural Language Processing (NLP) including information retrieval and machine translation, Computer Vision, or classification models utilizing Boosting/Bagging or Deep Neural Networks.