Applied Scientist BRP Payment Risk ML
Applied Scientist BRP Payment Risk ML
Posted on :
27-04-2025
Employer Active
1 Vacancy
Job Alert
You will be updated with latest job alerts via emailValid email field required
Send jobs
Share
Send me jobs like this
Job Alert
You will be updated with latest job alerts via emailValid email field required
Send jobs
Yearly Salary
$ 136000 - 223400
Vacancy
1 Vacancy
Posted on :
27-04-2025
Job 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 stateoftheart algorithms to solve real world problems
Do you like to own endtoend 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 Amazons 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 realtime 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
PhD or Masters 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 highperformance computing
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.
Los Angeles County applicants: Job duties for this position include: work safely and cooperatively with other employees supervisors and staff; adhere to standards of excellence despite stressful conditions; communicate effectively and respectfully with employees supervisors and staff to ensure exceptional customer service; and follow all federal state and local laws and Company policies. Criminal history may have a direct adverse and negative relationship with some of the material job duties of this position. These include the duties and responsibilities listed above as well as the abilities to adhere to company policies exercise sound judgment effectively manage stress and work safely and respectfully with others exhibit trustworthiness and professionalism and safeguard business operations and the Companys reputation. Pursuant to the Los Angeles County Fair Chance Ordinance we will consider for employment qualified applicants with arrest and conviction records.
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 for more information. If the country/region youre applying in isnt 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 $136000/year in our lowest geographic market up to $223400/year in our highest geographic market. Pay is based on a number of factors including market location and may vary depending on jobrelated knowledge skills and experience. Amazon is a total compensation company. Dependent on the position offered equity signon 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.
Are you excited by the prospect of analyzing and modeling terabytes of data and creating stateoftheart algorithms to solve real world problems
Do you like to own endtoend 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 Amazons 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 realtime 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
PhD or Masters 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 highperformance computing
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.
Los Angeles County applicants: Job duties for this position include: work safely and cooperatively with other employees supervisors and staff; adhere to standards of excellence despite stressful conditions; communicate effectively and respectfully with employees supervisors and staff to ensure exceptional customer service; and follow all federal state and local laws and Company policies. Criminal history may have a direct adverse and negative relationship with some of the material job duties of this position. These include the duties and responsibilities listed above as well as the abilities to adhere to company policies exercise sound judgment effectively manage stress and work safely and respectfully with others exhibit trustworthiness and professionalism and safeguard business operations and the Companys reputation. Pursuant to the Los Angeles County Fair Chance Ordinance we will consider for employment qualified applicants with arrest and conviction records.
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 for more information. If the country/region youre applying in isnt 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 $136000/year in our lowest geographic market up to $223400/year in our highest geographic market. Pay is based on a number of factors including market location and may vary depending on jobrelated knowledge skills and experience. Amazon is a total compensation company. Dependent on the position offered equity signon 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.
Employment Type
Full-Time
Key Skills
Report This Job
Disclaimer: Drjobpro.com is only a platform that connects job seekers and employers. Applicants are advised to conduct their own independent research into the credentials of the prospective employer.We always make certain that our clients do not endorse any request for money payments, thus we advise against sharing any personal or bank-related information with any third party. If you suspect fraud or malpractice, please contact us via contact us page.
