Sr. Data Scientist, Amazon Pay Data Products
Amazon Web Services (AWS) (company site, opens in a new tab)5+ yrsBengaluruOn-siteDirect career pageEst. 35–60 LPA
Posted on 18 Sept
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Job description
Structured overview of role & requirements
About This Role
- Lead end-to-end machine learning projects using PyTorch, AWS SageMaker, and related ML frameworks to deliver scalable AI solutions.
- Design, implement, and optimize statistical models and deep learning solutions with a focus on MLOps pipelines, including model training, evaluation, deployment, and monitoring using tools like MLflow and Docker.
- Partner with stakeholders to translate business problems into technical solutions, develop business intelligence applications, lead technical initiatives, and mentor junior data scientists.
Minimum Requirements
- Minimum 4 years of experience as a data scientist.
- 5+ years experience with data querying and scripting languages such as SQL and Python; experience with statistical software like R.
- Proficient with AWS technology stack including AWS Redshift, S3, EC2, Glue and ML deployment tools (CodePipeline, Lambda, Step Functions).
- Experience building end-to-end machine learning solutions that generate measurable business impact.
Ideal Candidate Profile
- Experienced in managing complex ML lifecycle including MLOps, containerization (Docker), hyperparameter tuning, and model monitoring at scale.
- Skilled in modern large language models (LLM) frameworks and generative AI applications, indicating ability to work on cutting-edge AI products.
- Able to operate across cross-functional teams and communicate complex ML concepts to technical and non-technical stakeholders effectively.