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Description

Do you want to join an innovative team of scientists who use machine learning and statistical techniques to help Amazon provide the best customer experience by preventing eCommerce fraud?

Are you excited by the prospect of analyzing and modeling terabytes of data and creating state-of-the-art algorithms to solve real world problems?

Do you like to own end-to-end business problems/metrics and directly impact the profitability of the company? Do you enjoy collaborating in a diverse team environment?

If yes, then you may be a great fit to join the Amazon Buyer Risk Prevention (BRP) Machine Learning group. We are looking for a talented scientist who is passionate to build advanced algorithmic systems that help manage safety of millions of transactions every day.

Key job responsibilities

Use machine learning and statistical techniques to create scalable risk management systems

Learning and understanding large amounts of Amazon’s historical business data for specific instances of risk or broader risk trends

Design, development and evaluation of highly innovative models for risk management

Working closely with software engineering teams to drive real-time model implementations and new feature creations

Working closely with operations staff to optimize risk management operations,

Establishing scalable, efficient, automated processes for large scale data analyses, model development, model validation and model implementation

Tracking general business activity and providing clear, compelling management reporting on a regular basis

Research and implement novel machine learning and statistical approaches

Basic Qualifications

- PhD, or Master's degree and 4+ years of CS, CE, ML or related field experience

- 2+ years of building models for business application experience

- Experience programming in Java, C++, Python or related language

- Experience in any of the following areas: algorithms and data structures, parsing, numerical optimization, data mining, parallel and distributed computing, high-performance computing

Preferred Qualifications

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

- 5+ years of industry experience in predictive modeling and analysis

- Strong Machine Learning breadth and depth

- Strong skills with SQL Strong skills with Spark/Python/Perl (or similar)

- Ability to think creatively and solve problems

- Good written and spoken communication skills

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

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.

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.