Want to stop fraudsters and make a direct multi-million dollar impact to Amazon's bottom line Come join the AWS Fraud Prevention team and help us fight fraud and financial crimes.The mission of the Fraud Prevention Team is to keep the AWS platform a safe and trusted place for our customers and partners worldwide and for all services. Fraudsters are continually looking for new ways to steal from companies. We invent new techniques to detect and stop these bad actors, leveraging the latest in modeling (ML, AI) and enforcement.As an Applied Scientist in AWS, you’ll be leading us in making critical and time sensitive decisions that impact customers. You’ll use your machine learning expertise to build solutions that can scale and solve the business problem, and your engineering experience to build systems that take those solutions to production; it's an exciting opportunity to apply data science to help improve detection accuracy, containment strategy, and ultimate enforcement activity. It’s fast paced, data driven, and impactful.Key job responsibilitiesThe position requires hands-on expertise in Analytics to identify and isolate issues, Statistical Modeling and traditional Machine Learning, the ability to write queries to aid in data extraction, and the ability to productionalize models.. This role is a self sufficient scientist that can source data, build and evaluate models, and ultimately take those models and rules to deployment. You should have excellent communication skills and be able to work with stakeholders at all levels. Above all you should be a passionate, hard-working and creative person who loves business, loves solving difficult problems and doesn’t mind getting involved in the details.A day in the lifeAt AWS Fraud Prevention, you will collaborate with a diverse group of internal stakeholders, including fraud operations, AWS service teams, and the Data Platform, to identify and address fraud vulnerabilities. You will have the opportunity to enhance our existing models and develop new ones that have a direct impact on the business. Your role will also allow you to leverage your customer-obsession skills by thoughtfully considering the user experience and ensuring it is not adversely affected by the mechanisms you design. If you are passionate about working with large-scale data, we offer ample opportunities to do so.About the teamOur team plays a crucial role in safeguarding secure and profitable business operations. Our mission is to position AWS as the most cost-effective and user-friendly cloud service provider by protecting legitimate customer experiences from the financial, operational, and reputational impacts of fraudulent activities. We develop services that prevent, detect, contain, and mitigate the actions of fraudulent and malicious users. As part of an analytics-driven team, you will leverage large-scale data to inform business decisions, respond to fraud, and automate decision-making at scale.Utility Computing (UC)AWS Utility Computing (UC) provides product innovations from foundational services such as Amazon’s Simple Storage Service (S3) and Amazon Elastic Compute Cloud (EC2), to consistently released new product innovations that continue to set AWS’s services and features apart in the industry. As a member of the UC organization, you’ll support the development and management of Compute, Database, Storage, Internet of Things (Iot), Platform, and Productivity Apps services in AWS, including support for customers who require specialized security solutions for customers who require specialized security solutions for their cloud services.Our team is dedicated to supporting new members. We have a broad mix of experience levels and tenures, and we’re building an environment that celebrates knowledge-sharing and mentorship. Our senior members enjoy one-on-one mentoring and thorough, but kind, code reviews. We care about your career growth and strive to assign projects that help our team members develop your engineering expertise so you feel empowered to take on more complex tasks in the future.Diverse ExperiencesAWS values diverse experiences. Even if you do not meet all of the qualifications and skills listed in the job description, we encourage candidates to apply. If your career is just starting, hasn’t followed a traditional path, or includes alternative experiences, don’t let it stop you from applying.About AWSAmazon Web Services (AWS) is the world’s most comprehensive and broadly adopted cloud platform. We pioneered cloud computing and never stopped innovating that’s why customers from the most successful startups to Global 500 companies trust our robust suite of products and services to power their businesses.Inclusive Team CultureHere at AWS, it’s in our nature to learn and be curious. Our employee-led affinity groups foster a culture of inclusion that empower us to be proud of our differences. Ongoing events and learning experiences, including our Conversations on Race and Ethnicity (CORE) and AmazeCon (gender diversity) conferences, inspire us to never stop embracing our uniqueness.Work/Life BalanceWe value work-life harmony. Achieving success at work should never come at the expense of sacrifices at home, which is why we strive for flexibility as part of our working culture. When we feel supported in the workplace and at home, there’s nothing we can’t achieve in the cloud.Mentorship & Career GrowthWe’re continuously raising our performance bar as we strive to become Earth’s Best Employer. That’s why you’ll find endless knowledge-sharing, mentorship and other career-advancing resources here to help you develop into a better-rounded professional.BASIC QUALIFICATIONS- PhD, or Master's degree and 4+ years of CS, CE, ML or related field experience- 3+ years of building models for business application experience- 5+ years of designing experiments and statistical analysis of results experience- Experience programming in Java, C++, Python or related language- PhD or equivalent Master's degree in Machine Learning, Artificial Intelligence, Mathematics, Statistics, Computer Science, Operations Research or in another highly quantitative field- 3+ years of hands-on industry experience working with large scale ML problems, end to end- Ability to develop and deploy (in partnership with engineers) Machine Learning models that power specific applications- 5+ years with Statistical Analysis and Modeling tools like Python, R, Matlab or similar- Skilled in various Statistical and traditional Machine Learning methods such as tree-based models- Able to write SQL scripts for analysis and reporting- Superior verbal and written communication and presentation skills, ability to convey rigorous mathematical concepts and considerations to non-experts- Enjoys working in a team environmentPREFERRED QUALIFICATIONS- Experience using Unix/Linux- Experience in professional software development- 4+ years of applied ML experience in a quantitative filed- Solid software development experience- Experience with Natural Language Processing and Deep Learning Models in general- Knowledge of AWS Infrastructure, Redshift- Knowledge of AWS services such as EC2, Sagemaker- Predictive Analytics- Any Hadoop, NoSQL Database & TechnologyAmazon 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.Our compensation reflects the cost of labor across several US geographic markets. The base pay for this position ranges from $136,000/year in our lowest geographic market up to $223,400/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.