Data Scientist

Amazon’s Data Science teams tackle some of the most complex challenges in e‑commerce, cloud computing, logistics, and artificial intelligence. As a Data Scientist, you will work on massive, real‑world datasets to define new metrics, build predictive models, and create tools that directly influence customer experience and business outcomes. You’ll collaborate with engineers, product managers, and research scientists to translate ambiguous business questions into rigorous analytical frameworks, then deploy scalable machine‑learning solutions that run in production at Amazon scale.

Key focus areas include demand forecasting, personalization and recommendation systems, fraud detection, supply‑chain optimization, natural language understanding, and computer vision. You’ll have access to petabytes of structured and unstructured data, state‑of‑the‑art compute infrastructure (including AWS SageMaker, Redshift, and custom ML platforms), and a culture that encourages experimentation and rapid iteration. Amazon’s “Day 1” mindset means you’ll be expected to invent and simplify, driving measurable impact from day one.

We value diverse perspectives and encourage candidates from all quantitative backgrounds—statistics, computer science, economics, physics, operations research, and related fields. Whether you’re developing a new ranking algorithm for search, optimizing last‑mile delivery routes, or building generative AI models for Alexa, your work will reach hundreds of millions of customers globally.

• PhD or Master’s degree in Computer Science, Statistics, Mathematics, Economics, Physics, or a related quantitative field
• 3+ years of industry experience applying machine learning and statistical modeling to large‑scale problems
• Proficiency in Python (or Java/Scala) and SQL; experience with Spark, TensorFlow, PyTorch, or similar ML frameworks
• Strong track record of taking projects from concept to production, including model training, evaluation, deployment, and monitoring
• Excellent communication skills: ability to translate technical findings into actionable insights for non‑technical stakeholders
• Experience with A/B testing, causal inference, or experimental design is a plus
• Familiarity with cloud platforms (AWS preferred) and distributed computing concepts