Description Are you excited by the idea of developing personalized experiences for Amazon customers as they shop? Are you looking for new challenges and to solve hard science problems while applying state-of-the-art recommendation system modeling and GenAI techniques? Join us and you'll help millions of customers make informed purchase decisions while also advancing the state of Amazon's science by publishing research!

Key job responsibilities Participate in the design, development, evaluation, deployment and updating of data-driven models for shopping personalization.

Develop and test recent signals for improving recommendation models

Use supervised and uplift learning algorithms to improve customer experience

Contribute to production code and science tooling

Design A/B tests and conduct statistical analysis on their results

Work with distributed machine learning and statistical algorithms to harness enormous volumes of data at scale to serve our customers

Work closely with internal stakeholders like the business teams, engineering teams and partner teams and align them with respect to your focus area

Present and publish science research internally and externally, contributing to Amazon's science community

Mentor junior engineers and scientists.

About The Team Our team's mission is to surface the right payments-related recommendations to customers at the right time, helping create a rewarding and successful shopping experience for Amazon's customers.



Our team's culture is highly collaborative, with an emphasis on supporting each other and learning from one another. We dedicate time each week to focus on personal development and expanding our knowledge as a team.

We also highly value having a big impact, both for Amazon's business and for our customers.

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 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 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 https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you’re applying in isn’t listed, please contact your Recruiting Partner.

📌 Applied Scientist, MAPLE - Recommender System (Bengaluru)
🏢 Amazon Science
📍 Bengaluru