Senior Applied Scientist , Buyer Risk Prevention (BRP)

Amazon Science; Bengaluru; On-site; INR 3,000,000 - 4,200,000; Full time

Job summary

Amazon Science's BRP Machine Learning team seeks a Senior Applied Scientist to define and drive the scientific direction of large-scale risk management systems that safeguard millions of transactions daily. You will design and deploy advanced ML solutions and influence cross-team strategy.

You will mentor junior scientists, explore GenAI/LLMs for risk evaluation, and communicate insights to senior leadership while staying ahead of emerging scientific trends.

Qualifications

• 3+ years of building machine learning models for business application experience.
• PhD, or Master's degree and 5+ years of applied research experience.
• Experience programming in Java, C++, Python or related language.
• Experience with neural deep learning methods and machine learning.

Responsibilities

• Lead the end-to-end scientific strategy for large-scale fraud and risk modeling initiatives.
• Define problem statements, success metrics, and long-term modeling roadmaps in partnership with business and engineering leaders.
• Design, develop, and deploy highly scalable machine learning systems in real-time production environments.
• Drive innovation using advanced ML, deep learning, and GenAI/LLM technologies to automate and transform risk evaluation.
• Influence system architecture and partner with engineering teams to ensure robust, scalable implementations.
• Establish best practices for experimentation, model validation, monitoring, and lifecycle management.
• Mentor and raise the technical bar for junior scientists through reviews, technical guidance, and thought leadership.
• Communicate complex scientific insights clearly to senior leadership and cross-functional stakeholders.
• Identify emerging scientific trends and translate them into impactful production solutions.

Skills

Machine learning modeling

Deep learning

Programming (Python/Java/C++)

Education

PhD or MS with 5+ years of applied research

Tools

R

scikit-learn

Spark MLLib

MxNet

TensorFlow

NumPy

SciPy

Job description

Description

Do you want to lead the development of advanced machine learning systems that protect millions of customers and power a trusted global eCommerce experience?

Are you passionate about modeling terabytes of data, solving highly ambiguous fraud and risk challenges, and driving step-change improvements through scientific innovation?

If so, the Amazon Buyer Risk Prevention (BRP) Machine Learning team may be the right place for you.

We are seeking a Senior Applied Scientist to define and drive the scientific direction of large-scale risk management systems that safeguard millions of transactions every day. In this role, you will lead the design and deployment of advanced machine learning solutions, influence cross-team technical strategy, and leverage emerging technologies—including Generative AI and LLMs to build next-generation risk prevention platforms.

Key job responsibilities

• Lead the end-to-end scientific strategy for large-scale fraud and risk modeling initiatives
• Define problem statements, success metrics, and long-term modeling roadmaps in partnership with business and engineering leaders
• Design, develop, and deploy highly scalable machine learning systems in real-time production environments
• Drive innovation using advanced ML, deep learning, and GenAI/LLM technologies to automate and transform risk evaluation
• Influence system architecture and partner with engineering teams to ensure robust, scalable implementations
• Establish best practices for experimentation, model validation, monitoring, and lifecycle management
• Mentor and raise the technical bar for junior scientists through reviews, technical guidance, and thought leadership
• Communicate complex scientific insights clearly to senior leadership and cross-functional stakeholders
• Identify emerging scientific trends and translate them into impactful production solutions

Basic Qualifications

• 3+ years of building machine learning models for business application experience
• PhD, or Master's degree and 5+ years of applied research experience
• Experience programming in Java, C++, Python or related language
• Experience with neural deep learning methods and machine learning

Preferred Qualifications

• Experience with modeling tools such as R, scikit-learn, Spark MLLib, MxNet, Tensorflow, numpy, scipy etc.
• Experience with large scale distributed systems such as Hadoop, Spark etc.

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