Applied Scientist, Denied Entity Screening at AWS Compliance & Security Assurance

Join Amazon’s mission : At Amazon, security plays a vital role in maintaining customer trust and creating exceptional customer experiences. Our team aims to prevent restricted entities from interacting with Amazon businesses. We develop automated systems to detect and prevent transactions with prohibited entities by leveraging advanced algorithms and machine learning techniques. With over a billion events screened daily, we’re on an exciting journey to enhance our detection and resolution systems through Machine Learning (ML) and Generative AI technologies.

Your role : We are looking for an innovative Applied Scientist to help address challenging problems in machine learning and artificial intelligence. You will collaborate closely with engineers, data scientists, and domain experts to define and develop cutting-edge ML/AI solutions that enhance customer experiences. If you possess a strong technical background, an entrepreneurial spirit, and a commitment to innovation, we want to hear from you!

Key Responsibilities:

• Develop and implement novel ML/AI models and systems for essential products and services.
• Collaborate across teams to understand business requirements, customer needs, and technical limits.
• Quickly prototype, test, and refine ML/AI solutions, adapting based on data-driven results and feedback.
• Effectively communicate complex technical concepts to both technical and non-technical stakeholders.
• Mentor and cultivate a team of skilled ML scientists and engineers.
• Stay informed about the latest trends in AI/ML and identify emerging opportunities.

A typical day:

• Review model performance metrics, pinpointing areas for improvement.
• Engage in brainstorming sessions with your cross-functional team to devise new architectures and strategies.
• Analyze complex datasets using sophisticated statistical and AI techniques to extract insights.
• Prototype new models, conducting experiments to optimize their performance.
• Prepare presentations to share research findings and recommendations with product and engineering teams.
• Provide mentorship to junior data scientists, guiding them on coding best practices and problem-solving methods.

Why Amazon Security? At Amazon, we prioritize security to uphold customer trust and deliver exceptional experiences across our products and services.

Work-Life Balance: We believe in achieving work-life harmony. Success should never come at the expense of personal well-being, and we foster flexible work arrangements.

Inclusive Culture: In Amazon Security, we celebrate diversity and embrace unique perspectives. We believe that tackling complex security challenges requires a variety of ideas and voices.

Training and Career Growth: We continuously strive to elevate our performance standards. You will find numerous resources for knowledge-sharing, training, and career advancement.

Qualifications:

• Minimum of 3 years experience in developing models for business applications.
• PhD or Master's degree with at least 4 years in computer science, computer engineering, machine learning, or related fields.
• Experience with publications or patents in high-ranking peer-reviewed journals or conferences.
• Proficiency in programming languages such as Java, C++, or Python.
• Expertise in algorithms, data structures, parsing, numerical optimization, data mining, and high-performance computing.

Preferred Qualifications:

• Familiarity with Unix/Linux environments.
• Background in professional software development.

Amazon is an equal opportunity employer and does not discriminate against individuals based on protected veteran status, disability, or other legally protected attributes.

This position's base salary range is $142,800.00 - $193,200.00 annually. Compensation includes sign-on bonuses and stock options. Final compensation is influenced by experience, qualifications, and location. Amazon offers comprehensive benefits including health insurance, 401(k) matching, generous paid time off, and parental leave. Explore our benefits further.

Location: Dallas, TX or Seattle, WA