Applied Scientist, Buyer Abuse Prevention ML

Applied Scientist, Buyer Abuse Prevention ML

Job ID: 2748770 | Amazon.com Services LLC

Amazon.com’s Buyer Risk Prevention's (BRP) mission is to make Amazon the safest and most trusted place worldwide to transact online. BRP safeguards every financial transaction across all Amazon sites. As such, BRP designs and builds the software systems, risk models, and operational processes that minimize risk and maximize trust in Amazon.com. The BRP organization is looking for an Applied Scientist for the Buyer Abuse team, whose mission is to combine advanced analytics with investigator insight to create mechanisms to proactively and reactively reduce the impact of abuse across Amazon.

Key Job Responsibilities

As an Applied Scientist, you will be responsible for modeling complex problems, discovering insights, and building cutting edge risk algorithms that identify opportunities through statistical models, machine learning, and visualization techniques to improve operational efficiency, reduce monetary losses, and improve customer trust.

You will need to collaborate effectively with business and product leaders within BRP and cross-functional teams to build scalable solutions against high organizational standards. The candidate should be able to apply a breadth of tools, data sources, and ML techniques to answer a wide range of high-impact business questions and proactively present new insights in a concise and effective manner.

The candidate should be an effective communicator capable of independently driving issues to resolution and communicating insights to non-technical audiences. This is a high impact role with goals that directly impact the bottom line of the business.

Responsibilities

1. Invent, implement, and deploy state of the art machine learning algorithms and systems
2. Build prototypes and explore conceptually new solutions
3. Define and conduct experiments to validate/reject hypotheses, and communicate insights and recommendations to Product and Tech teams
4. Take ownership of how ML solutions impact Amazon resources and Customer experience
5. Develop efficient data querying infrastructure for both offline and online use cases
6. Collaborate with cross-functional teams from multidisciplinary science, engineering, and business backgrounds to enhance current automation processes
7. Learn and understand a broad range of Amazon’s data resources and know when, how, and which to use and which not to use.
8. Research and implement novel machine learning and statistical approaches
9. Maintain technical documentation and communicate results to diverse audiences with effective writing, visualizations, and presentations

BASIC QUALIFICATIONS

1. PhD, or Master's degree and 4+ years of CS, CE, ML or related field experience
2. Experience programming in Java, C++, Python or related language
3. 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

1. Experience using Unix/Linux
2. Experience in professional software development

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

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 $222,200/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 This position will remain posted until filled. Applicants should apply via our internal or external career site.