Applied Scientist II, Buyer Risk Prevention (BRP)

Amazon Science; Bengaluru; Vor Ort; INR 1.800.000 - 3.000.000; Vollzeit

Zusammenfassung

Amazon Science is seeking an Applied Scientist to design, develop, and deploy advanced machine learning systems for Buyer Risk Prevention. You will own models from problem formulation to production, analyzing terabytes of data and deploying scalable algorithms to protect Amazon customers and improve profitability.

The role emphasizes leveraging GenAI and LLMs, collaborating with software teams, and delivering measurable business impact through robust risk assessment and fraud detection.

Qualifikationen

• 3+ years of building models for business applications.
• PhD or Master’s degree in a relevant field.
• Experience in patents or publications at top-tier conferences or journals.
• Proficiency in Java, C++, Python, or related languages.
• Experience in algorithms, data structures, numerical optimization, data mining, parallel and distributed computing.

Aufgaben

• Own end-to-end development of ML models for large-scale risk management systems.
• Analyze large volumes of historical and real-time data to identify fraud patterns and risk trends.
• Design, develop, validate, and deploy models to production environments.
• Apply GenAI/LLM technologies to automate risk evaluation and improve efficiency.
• Collaborate with software engineering teams to implement scalable real-time solutions.
• Translate risk insights into measurable business impact with stakeholders.
• Establish automated processes for data analysis, model experimentation, validation and monitoring.
• Track model performance and communicate insights to technical and non-technical stakeholders.

Kenntnisse

Python

Java

C++

Machine Learning

Statistics

Ausbildung

PhD

Master's degree

Tools

Unix/Linux

Git

Jobbeschreibung

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?

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
  

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