Sr. Applied Scientist, Denied Party Screening (DPS), AWS Compliance & Security Assurance

At Amazon, security is central to maintaining customer trust and delivering delightful customer experiences. Our mission is to prevent denied entities from transacting with Amazon businesses. We build automatic mechanisms to detect and prevent prohibited transactions with denied entities using a diverse set of algorithms and machine learning techniques. We screen over a billion events every day and develop algorithms which are able to scale and detect suspicious entities . We are still Day 1 and have an exciting road map to build Machine Learning (ML) and Generative AI (LLM) powered detection and resolution systems to help scale Amazon for years to come.

We are seeking an Sr. Applied Scientist to join our team and help tackle challenging problems at the forefront of machine learning and artificial intelligence. Working closely with a multidisciplinary team of engineers, data scientists, and domain experts, you will play a crucial role in defining innovative ML/AI-powered customer experiences and solutions. If you have an entrepreneurial mindset, the technical depth to deliver impactful results, and a passion for innovation, we want to hear from you.

Key job responsibilities
In this role, you will:
• Drive the research, design, and development of novel ML/AI models and systems to power critical products and services
• Collaborate cross-functionally to deeply understand business requirements, customer needs, and technical constraints
• Rapidly prototype, test, and iterate on ML/AI solutions, iterating quickly based on data and feedback
• Communicate complex technical concepts to technical and non-technical stakeholders • Mentor and grow a team of talented ML scientists and engineers
• Stay up-to-date on the latest advancements in AI/ML and identify opportunities to apply emerging techniques

A day in the life
- Starting the day by reviewing the latest model performance metrics and identifying areas for improvement
- Brainstorming new architectures and approaches with your cross-functional team during a whiteboard session
- Diving deep into a complex dataset, leveraging advanced statistical and AI techniques to uncover hidden insights
- Prototyping a new model and running a series of experiments to optimize its performance
- Preparing a presentation to pitch your latest research findings and recommendations to product and engineering leaders
- Mentoring junior scientists, providing guidance on coding best practices and problem-solving strategies

About the team
Why Amazon Security
At Amazon, security is central to maintaining customer trust and delivering delightful customer experiences. Our organization is responsible for creating and maintaining a high bar for security across all of Amazon’s products and services.

Work/Life Balance
We value work-life harmony. Achieving success at work should never come at the expense of sacrifices at home, which is why flexible work hours and arrangements are part of our culture. When we feel supported in the workplace and at home, there’s nothing we can’t achieve.

Inclusive Team Culture
In Amazon Security, it’s in our nature to learn and be curious. Ongoing DEI events and learning experiences inspire us to continue learning and to embrace our uniqueness. Addressing the toughest security challenges requires that we seek out and celebrate a diversity of ideas, perspectives, and voices.

Training and Career growth
We’re continuously raising our performance bar as we strive to become Earth’s Best Employer. That’s why you’ll find endless knowledge-sharing, training, and other career-advancing resources here to help you develop into a better-rounded professional.

Basic Qualifications

- 5+ years of building machine learning models for business application experience
- PhD, or Master's degree and 6+ years of applied research experience
- Experience programming in Java, C++, Python or related language
- Experience with neural deep learning methods and machine learning

Preferred Qualifications

- Experience with modeling tools such as R, scikit-learn, Spark MLLib, MxNet, Tensorflow, numpy, scipy etc.
- Experience with large scale distributed systems such as Hadoop, Spark etc.

Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status.

Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you’re applying in isn’t listed, please contact your Recruiting Partner.

The base salary range for this position is listed below. Your Amazon package will include sign-on payments and restricted stock units (RSUs). Final compensation will be determined based on factors including experience, qualifications, and location. Amazon also offers comprehensive benefits including health insurance (medical, dental, vision, prescription, Basic Life & AD&D insurance and option for Supplemental life plans, EAP, Mental Health Support, Medical Advice Line, Flexible Spending Accounts, Adoption and Surrogacy Reimbursement coverage), 401(k) matching, paid time off, and parental leave. Learn more about our benefits at https://amazon.jobs/en/benefits.

USA, WA, Seattle - 167,100.00 - 226,100.00 USD annually