At Amazon, we are obsessed with customer trust. Amazon Security enables Amazon's business leaders to build and operate securely while protecting the confidentiality and integrity of Amazon and customer data. We assess risk, classify data and systems, detect intrusion, and drive mitigation at scale. Veritas is Amazon's single source of truth for applications and services and the resources that make them up, spanning both Stores/Devices (SDO) and AWS. Security teams across Amazon rely on Veritas to understand attack paths, assign issue ownership, track the flow of sensitive data, and reason about risk across one of the largest and most diverse technology footprints in the world. We are seeking a talented, self-directed Senior Data Scientist to work on cutting-edge security technologies. You will take the lead on large, ambiguous problems that have not been solved before - defining both the problem and the solution approach autonomously. You will design and run experiments, research new algorithms, and find new ways to protect Amazon's customer trust. You will work closely with talented software engineers and security engineers who transform your prototypes and models into production. You should thrive in ambiguous environments and enjoy fast-paced settings where learning new concepts quickly is essential. You leverage exceptional technical expertise, strong statistical skills, and data acumen to analyze large volumes of business data and make Amazon safer. Your strong communication skills enable you to influence across multiple teams and to work effectively with both business and technical partners, including senior leadership. Key job responsibilities - Define problems and solution approaches autonomously in ambiguous, open-ended security problem spaces where no established pattern exists. - Process and analyze large data sets using the full range of techniques required, selecting the ideal method from a wide range of data science disciplines. - Deliver scalable models that analyze large data sets efficiently. - Build mathematical models to detect and classify specific data elements with high accuracy. - Prototype models in high-level modeling languages such as R, or in software languages such as Python. A software team will partner with you to transform prototypes into production. - Take the lead on large projects that require both business and technical domain expertise, delivering significant benefit to the business. - Influence multiple teams and build consensus across business, science, and engineering stakeholders; advise senior managers and directors on data-driven security decisions. - Mentor and develop other scientists; perform data science technical assessments and participate in science and data-engineering code reviews. - Create, enhance, and maintain technical documentation, and present findings to other scientists and business leaders, keeping teams current on relevant scientific advancements.