Sr Applied Scientist, Denied Party Screening

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 outstanding 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 cutting-edge 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

1. Starting the day by reviewing the latest model performance metrics and identifying areas for improvement

2. Brainstorming new ML architectures and approaches with your cross-functional team during a whiteboard session

3. Diving deep into a complex dataset, leveraging advanced statistical and ML techniques to uncover hidden insights

4. Prototyping a new ML model and running a series of experiments to optimize its performance

5. Preparing a presentation to pitch your latest research findings and recommendations to product and engineering leaders

6. Mentoring a junior data scientist, 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

- 4+ 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

- A PhD in Computer Science, Machine Learning, Statistics, Operations Research or relevant field

- Strong Machine Learning breadth and depth

- Demonstrated track record of cultivating strong working relationships and driving collaboration across multiple technical and business teams

Amazon is committed to a diverse and inclusive workplace. Amazon is an equal opportunity employer and does not discriminate on the basis of race, national origin, gender, gender identity, sexual orientation, protected veteran status, disability, age, or other legally protected status. For individuals with disabilities who would like to request an accommodation, please visit https://www.amazon.jobs/en/disability/us.

Our compensation reflects the cost of labor across several US geographic markets. The base pay for this position ranges from $150,400/year in our lowest geographic market up to $260,000/year in our highest geographic market. Pay is based on a number of factors including market location and may vary depending on job-related knowledge, skills, and experience. Amazon is a total compensation company. Dependent on the position offered, equity, sign-on payments, and other forms of compensation may be provided as part of a total compensation package, in addition to a full range of medical, financial, and/or other benefits. For more information, please visit https://www.aboutamazon.com/workplace/employee-benefits. This position will remain posted until filled. Applicants should apply via our internal or external career site.

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