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    Job · 20063024

    Amazon Prime Video logo

    Applied Scientist II, Buyer Risk Prevention (BRP)

    Amazon Prime Video · Not specified · onsite · Posted 20d ago

    Not disclosedFresherfulltimeSourced fromFoundit

    About a minute. You'll make an account on the way through.

    About this role

    Description

    Do you want to join an innovative team of scientists applying machine learning and advanced statistical techniques to protect Amazon customers and enable a trusted eCommerce experience

    Are you excited about modeling terabytes of data and building state-of-the-art algorithms to solve complex, real-world fraud and risk challenges

    Do you enjoy owning end-to-end machine learning problems, directly influencing customer experience and company profitability, while collaborating in a diverse, high-performing team

    If so, the Amazon Buyer Risk Prevention (BRP) Machine Learning team may be the right fit for you. We are seeking an Applied Scientist to design, develop, and deploy advanced algorithmic systems that safeguard millions of transactions every day.

    In this role, you will independently drive model development from problem formulation to production deployment, build scalable ML solutions, and leverage emerging technologies-including Generative AI and LLMs-to enhance fraud detection and next-generation risk prevention systems.

    Key job responsibilities
    Own end-to-end development of machine learning models for large-scale risk management systems

    Analyze large volumes of historical and real-time data to identify fraud patterns and emerging risk trends

    Design, develop, validate, and deploy innovative models to production environments

    Apply GenAI/LLM technologies to automate risk evaluation and improve operational efficiency

    Collaborate closely with software engineering teams to implement scalable, real-time model solutions

    Partner with operations and business stakeholders to translate risk insights into measurable impact

    Establish scalable and automated processes for data analysis, model experimentation, validation, and monitoring

    Track model performance and business metrics communicate insights clearly to technical and non-technical stakeholders
    Research and implement novel machine learning and statistical methodologies

    Basic Qualifications

    - 3+ years of building models for business application experience
    - PhD, or Master's degree
    - Experience in patents or publications at top-tier peer-reviewed conferences or journals
    - 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

    - Experience using Unix/Linux
    - Experience in professional software development
    - Experience in software development and delivery

    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 you're applying in isn't listed, please contact your Recruiting Partner.

    Sourced from foundit

    Skills

    high performance computingdata miningparsingLarge Language Models (LLMs)Numerical OptimizationUnixalgorithms and data structuresparallel and distributed computingPythonJavaGenerative AiLinux

    About Amazon Prime Video

    Amazon Prime Video logo

    Amazon Prime Video

    350

    employees

    2006

    20 years old

    Seattle

    United States

    ₹7L PA avg

    Avg at Amazon Prime Video

    About

    Prime Video is a mobile and web-based video platform. When you download titles to your iPhone, iPad, Tablet, or Android device, you can watch them offline on the Prime Video app.

    Employee ratings

    10 reviews

    3.8/ 5

    Culture

    4.0

    Career growth

    2.8

    Work-life

    4.1

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