Amazon’s offer-ranking team builds the machine learning systems that help customers see the right offers at the moment they are ready to buy. In this onsite role in Seattle, you will develop and operate ranking and recommendation models, run experiments that measure real customer and business impact, and help keep model performance strong as the marketplace changes.
This Data Scientist position supports large-scale decisioning across Amazon’s product catalog, from feature engineering through production deployment, with close collaboration across science, engineering, and product.
What you’ll do
- Build and own machine learning models that rank and recommend offers across Amazon’s product catalog, including work from feature engineering through production deployment.
- Design and analyze A/B experiments to quantify the effects of algorithm changes on customer experience, seller competition, and business outcomes.
- Mine large-scale datasets to uncover patterns and signals (including seller behavior, pricing dynamics, and fulfillment performance) that improve best-offer prediction for each customer.
- Translate business questions into well-defined data science problems, and communicate results clearly to engineers, product managers, and leadership.
- Partner with software engineers to operationalize models at scale, supporting reliable performance under high-traffic, low-latency conditions.
- Monitor model performance over time , diagnose degradation, and iterate to maintain ranking quality as the marketplace evolves.
Required qualifications
- 1+ years of experience with data querying languages (e.g., SQL), scripting languages (e.g., Python), or statistical and mathematical software (e.g., R, SAS, Matlab, etc.).
- 2+ years of experience as a data/research scientist, statistician, or quantitative analyst in an internet-based company working with complex and big data sources.
- 1+ years of creating or contributing to mathematical textbooks, research papers, or educational content.
- Master’s degree in Science, Technology, Engineering, or Mathematics (STEM), or equivalent experience in STEM.
Tools and technologies
- SQL, Python, R, SAS, Matlab, SPSS, S-PLUS
- Hadoop, Spark, Map-reduce, Hive
Preferred qualifications
- Ph.D. in STEM.
- Knowledge of statistical packages and business intelligence tools such as SPSS, SAS, S-PLUS, or R.
- Knowledge of machine learning concepts and their application to reasoning and problem-solving.
- Experience with clustered data processing such as Hadoop, Spark, Map-reduce, and Hive.
- Experience working with or evaluating AI systems.
- Experience applying quantitative analysis to solve business problems and make data-driven business decisions.
- Experience communicating complex concepts through written and verbal communication.
About the team
- Owns a consequential algorithm that determines which offer a customer sees when they are ready to buy.
- Brings together scientists, engineers, and product managers focused on getting ranking right for customers and sellers.
- Moves fast, runs many experiments, and debates ideas openly.
- Values rigorous science, shipping important work, and avoiding shortcuts that erode customer trust.
Compensation and location
Location: Seattle, WA (onsite). Compensation: USD 108,300 - 160,000 per year.
Benefits
- Sign-on payments
- Restricted stock units (RSUs)
- Health insurance (medical, dental, vision, prescription, Basic Life & AD&D insurance and option for Supplemental life plans, EAP, Mental Health Support, Medical Advice Line, Flexible Spending Accounts, Adoption and Surrogacy Reimbursement coverage)
- 401(k) matching
- Paid time off
- Parental leave