Applied Scientist , PAE

Description

Every time a customer checks out, a split-second decision determines which payment method appears, in what ranking, whether there is payment failure risk and how frictionless the experience feels. That decision touches 300MM+ customers and 2B+ monthly transactions — and you'll be the scientist building the intelligence behind it.

Every time a customer checks out, a split-second decision determines which payment method appears, in what ranking, whether there is payment failure risk and how frictionless the experience feels. That decision touches 300MM+ customers and 2B+ monthly transactions — and you'll be the scientist building the intelligence behind it.

Are you excited by the challenge of applying machine learning, GenAI, and real-time personalization to one of the highest-volume, lowest-latency decision systems at Amazon? Do you want to build models that directly move billions in revenue — predicting payment risk before it happens, recommending the right payment method at the right moment, and eliminating friction that customers shouldn't have to think about?
Join Payment Acceptance & Experience (PAE) Data Science, where you'll build the ML systems that power Amazon's Payment Experience Intelligence. You'll take models from conception to production alongside scientists, engineers, and product managers, shipping at a scale few teams in the industry can match.

• Build and ship ML systems at scale — design, develop, evaluate, deploy, and monitor ML models that personalize payment experiences for 300MM+ customers across 2B+ monthly transactions.
• Solve global problems once — develop worldwide models that scale across business lines and locales with minimal adaptation, and continuously improve model performance and ML architecture.
• Own the full lifecycle — contribute production-grade code and science tooling, from experimentation framework to deployed inference.
• Measure real impact — design A/B experiments, conduct rigorous statistical analysis, and translate results into product and business decisions.
• Ship with engineering and product partners — collaborate with SDEs to take models from prototype to production, and with business stakeholders to drive alignment on science-informed strategy.
• Advance the science — present and publish research internally and externally, contributing to Amazon's science community and raising the bar for the field.ommunity

Payment Acceptance and Experience's (PAE) mission is to build the most trusted, intuitive, and accessible payment experience on earth
. The team provides new and existing customers, anywhere in the world, the ability to pay on- and off-Amazon, with world-class ease of use, payment method variety, and security. The PAE Data Science team builds AI-native intelligence systems that improve payment experience, optimize marketing efficiency, automate operational workflows, and enable faster business decision-making across the payments ecosystem. It serves as a high-leverage, strategic engine advancing PAE's mission.

• Experience programming in Java, C++, Python or related language
• Experience with SQL and an RDBMS (e.g., Oracle) or Data Warehouse
• Currently has, or is in the process of obtaining, a Master's degree or above in Engineering, Computer Science, Machine Learning, Operations Research, Statistics, or related fields

• Experience implementing algorithms using both toolkits and self-developed code
• Have publications at top-tier peer-reviewed conferences or journals
• Currently has, or is in the process of obtaining, a PhD in Engineering, Computer Science, Machine Learning, Operations Research, Statistics, or related fields
• Experience building machine learning models or developing algorithms for business application

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