Data Scientist II, Data Scientist, IES CFX
Pubblicato il 20-10-2026 - Amazon in Asti
Are you passionate about applying machine learning and advanced statistical techniques to protect one of the world's largest online marketplaces? Do you want to be at the forefront of developing innovative solutions that improve Amazon's customers experience? Do you thrive in a collaborative environment where diverse perspectives drive breakthrough solutions?
If yes, we invite you to join the Amazon Customer Fulfillment & Prime analytics team. We're seeking an exceptional scientist who can revolutionize how we delight our customers. As a key member of our team, you'll develop and deploy machine learning systems that analyze millions of customer interactions daily, ensuring state of art experience for customers across 10 countries. Your work will directly impact the shopping experience for hundreds of millions of customers worldwide.
Key job responsibilities
- Ability to work independently across the end-to-end ML lifecycle: feature engineering, modeling, and MLOps to productionize models.
- Strong foundation in machine learning and statistical modeling.
- Experience deploying ML solutions into a production environment.
- Apply machine learning and statistical techniques to create scalable abuse-detection solutions that identify fraudulent customer behavior, rings of accounts, identity change, holistic customer risk, and marketplace manipulation schemes.
- Innovate with the latest GenAI technology to build highly automated solutions for efficient customer promotions.
- Collaborate with cross-functional teams to develop comprehensive ML/statistical models that scale to millions of customers across 10+ countries.
- Willing to travel to Mexico (MX) and Brazil (BR).
- Comfortable working CET hours to maintain overlap with Mexico and Brazil business teams.
About the team
- You'll be working closely with business partners, science and engineering teams to create end-to-end scalable machine learning solutions that address real-world problems.
- You will build scalable, e