Sr. Data Scientist, Amazon Pay Data Products

Amazon; Bengaluru; On-site; INR 4,000,000 - 7,000,000; Full time

Job summary

Amazon Pay Data Products team is seeking a Data Scientist III to drive ML innovations and lead high‑impact initiatives across the organization.

You will lead end‑to‑end ML projects using PyTorch, AWS SageMaker, and develop scalable MLOps pipelines, while mentoring junior data scientists and partnering with stakeholders to translate business problems into technical solutions.

Qualifications

• 5+ years of data querying languages (SQL) and scripting (Python) or statistical software experience.
• 4+ years of data scientist experience with ML projects.
• Experience with multinomial logistic regression or similar statistical models.
• Knowledge of AWS tech stack (Redshift, S3, EC2, Glue) and end-to-end ML solution delivery.

Responsibilities

• Lead end-to-end ML projects using PyTorch, AWS SageMaker, and other 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.
• Mentor junior data scientists and lead cross-functional collaboration.

Skills

SQL

Python

R

SAS

Matlab

Multinomial logistic regression

AWS

Redshift

S3

EC2

Glue

PyTorch

SageMaker

ML deployment

Tools

Docker

Kubernetes

CodePipeline

Lambda

Step Functions

MLflow

Job description

Sr. Data Scientist, Amazon Pay Data Products

Job ID: 3133798 | Amazon Pay (India) Private Limited

Amazon Pay strives to be Earth’s 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

• 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 Pay's 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.

Basic Qualifications

• 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

Preferred Qualifications

• 2+ years of data visualization using AWS QuickSight, Tableau, R Shiny, etc. experience
• Experience managing data pipelines

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Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status.