Job Description
Role Overview
nWe are looking for an Data Scientist/ AWS Engineer to join India Data Science team of DolFinTech, USA. The candidate must have at least 1 year of direct hands-on experience in developing, deploying, integrating, and monitoring Machine Learning models and processes on AWS. The candidate must have hands-on experience with Amazon SageMaker, AWS Lambda, API Gateway, S3, CloudWatch, and AWS-based ETL/data pipelines.
nKey Responsibilities
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- Develop, package, and deploy ML models using Amazon SageMaker .n
- Build and manage real-time SageMaker inference endpoints .n
- Develop AWS Lambda functions for model invocation and application integration.n
- Create and maintain REST/HTTP APIs using Amazon API Gateway .n
- Build and maintain ETL/data-processing pipelines on AWS using services such as S3, Glue, Lambda, Athena, and/or Step Functions.n
- Implement end-to-end ML scoring workflows such as:n
- Application/API → API Gateway → Lambda → SageMaker → Response n
- Implement logging, monitoring, and alerting using Amazon CloudWatch.n




- Monitor model/API performance, latency, failures, and production issues.n
- Troubleshoot AWS deployment, integration, and IAM/permission issues .n
- Support model and code versioning and deployment across Development, UAT/Staging, and Production environments.n
- Work with Data Scientists to convert notebook/prototype models into reliable production solutions.n

nMandatory Skills
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- Minimum 1 year of hands-on AWS experience n
- Solid hands-on experience with Amazon SageMaker, AWS Lambda , Amazon API Gateway, Amazon S3, Amazon CloudWatch, AWS IAM, AWS ETL/data-processing pipelines, AWS Glue, Athenan
- Strong Python and SQL skills.n
- Experience deploying ML models into production environments .n
- Experience creating and consuming REST APIs / JSON interfaces .n
- Experience with Git/version control .n
- Good understanding of ML models, feature engineering, model scoring, and model mo

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