Applied Scientist, Worldwide Installments

WW Installments is one of the fastest growing businesses within Amazon and we are looking for an Applied Scientist to join the team. This group has been entrusted with a massive charter that will impact every customer that visits Amazon.com. We are building the next generation of features and payment products that maximize customer enablement in a simple, transparent, and customer obsessed way. Through these products, we will deliver value directly to Amazon customers improving the shopping experience for hundreds of millions of customers worldwide. Our mission is to delight our customers by building payment experiences and financial services that are trusted, valued, and easy to use from anywhere in any way.

As an Applied Scientist within WW Installments, you will be responsible for building machine learning models and pipelines with direct customer impact. These models represent a core capability for WW Installments and businesses across Amazon. Your work will directly impact customers by influencing how they interact with financing options to make purchases. You will work across functions including data engineering, software development, and business to induce data driven decisions at every level of the organization.

Key job responsibilities

This role will be responsible for:

• Developing production machine learning models and pipelines for the WW Installments Fraud Detection team that directly impact customers.
• Apply expertise in machine learning to develop large-scale production systems that are deployed across Amazon businesses.
• Identify business opportunities, define and execute modeling approach, then deliver outcomes to various Amazon businesses with an Amazon-wide perspective for solutions.
• Lead the implementation of production ML from a scientific perspective including identifying consumer financial credit and fraud risks, key milestones, and paths to mitigate risks.
• Identifying new opportunities to influence business strategy and product vision using data science and machine learning.
• Continually improve the WW Installments ML roadmap automating and simplifying whenever possible.
• Coordinate support across engineers, scientists, and stakeholders to deliver ML pipelines, analytics projects, and build proof of concept applications.
• Work through significant business and technical ambiguity delivering on analytics roadmap across the team with autonomy.