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Applied Scientist, BRP Risk ML, BRP Risk ML

Job in San Diego, San Diego County, California, 92189, USA
Listing for: Amazon Inc.
Full Time position
Listed on 2026-10-08
Job specializations:
  • IT/Tech
    Machine Learning/ ML Engineer, Data Scientist
Salary/Wage Range or Industry Benchmark: 142800 - 193200 USD Yearly USD 142800.00 193200.00 YEAR
Job Description & How to Apply Below
Position: Applied Scientist, BRP Payment Risk ML, BRP Payment Risk ML

Job :  |  Services LLC

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
  • 3+ years of building models for business application experience
  • PhD, or Master's degree and 4+ years of CS, CE, ML or related field 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, GenAI, 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

USA, CA, San Diego -  -  USD annually

The base salary range for this position is listed below. Your Amazon package will include sign-on payments and restricted stock units (RSUs). Final compensation will be determined based on factors including experience, qualifications, and location. Amazon also offers comprehensive benefits including health insurance (medical, dental, vision, prescription, Basic Life & AD&D insurance and option for Supplemental life plans, EAP, Mental Health Support, Medical Advice Line, Flexible Spending Accounts, Adoption and Surrogacy Reimbursement coverage), 401(k) matching, paid time off, and parental leave.

Learn more about our benefits at (Use the "Apply for this Job" box below). .

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…

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