Amazon Pay strives to be Earths most customer-centric payments service. Our mission is to serve customers and merchant partners with the most trusted friction-less and rewarding payment solutions for their needs on and off Amazon.
We are seeking an exceptional Data Scientist III to drive innovation in machine learning and artificial intelligence solutions while leading high-impact initiatives across the organization.
Key job responsibilities
Technical Excellence
Lead end-to-end machine learning projects using PyTorch AWS SageMaker and other leading ML frameworks
Design and implement complex statistical models and deep learning solutions
Develop and optimize MLOps pipelines for model training evaluation and deployment
Experience with modern LLM frameworks and Generative AI applications
Expertise in Python R and related data science libraries
MLOps & Development
Build automated ML pipelines using AWS services (CodePipeline Lambda Step Functions)
Implement CI/CD practices for ML model deployment and monitoring
Create containerized solutions using Docker for scalable model deployment
Experience with model optimization and hyperparameter tuning using tools like Optuna
Integrate ML solutions with monitoring tools like MLflow
Business Impact & Leadership
Partner with stakeholders to translate business problems into technical solutions
Design and develop business intelligence applications for real-time insights
Lead technical initiatives and mentor junior data scientists
Drive cross-functional collaboration to deliver innovative solutions
Communicate complex technical concepts to non-technical audiences
About the team
The Amazon Pay Data Products team is a central unit that builds and maintains data products supporting Amazon Pays growth across multiple markets. We operate at scale processing 150M monthly transactions and managing 12 PB of data infrastructure.
Our team consists of Business Intelligence Engineers Data Engineers and Product Managers who develop and maintain standardized reporting data marts and self-service analytics tools. Our expanded capabilities cover data science and Gen AI wherein we have built our first suite of multi-agent systems.
- 5 years of data querying languages (e.g. SQL) scripting languages (e.g. Python) or statistical/mathematical software (e.g. R SAS Matlab etc.) experience
- 4 years of data scientist experience
- Experience with statistical models e.g. multinomial logistic regression
- Knowledge of AWS tech stack (e.g. AWS Redshift S3 EC2 Glue)
- Track record of developing end-to-end ML solutions that drive business impact
- 2 years of data visualization using AWS QuickSight Tableau R Shiny etc. experience
- Experience managing data pipelines
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