Job Description

Role Overview We are looking for an Data Scientist/ AWS Engineer to join India Data Science team of Dol FinTech, 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 Sage Maker, AWS Lambda, API Gateway, S3, Cloud Watch, and AWS-based ETL/data pipelines. Key Responsibilities Develop, package, and deploy ML models using Amazon Sage Maker . Build and manage real-time Sage Maker inference endpoints .
Develop AWS Lambda functions for model invocation and application integration. Create and maintain REST/HTTP APIs using Amazon API Gateway . Build and maintain ETL/data-processing pipelines on AWS using services such as S3, Glue, Lambda, Athena, and/or Step Functions.
Implement end-to-end ML scoring workflows such as: Application/API → API Gateway → Lambda → Sage Maker → Response Implement logging, monitoring, and alerting using Amazon Cloud Watch. Monitor model/API performance, latency, failures, and production issues.
Troubleshoot AWS deployment, integration, and IAM/permission issues . Support model and code versioning and deployment across Development, UAT/Staging,



and Production environments. Work with Data Scientists to convert notebook/prototype models into reliable production solutions.
Mandatory Skills Minimum 1 year of hands-on AWS experience Robust hands-on experience with Amazon Sage Maker, AWS Lambda , Amazon API Gateway, Amazon S3, Amazon Cloud Watch, AWS IAM, AWS ETL/data-processing pipelines, AWS Glue, Athena Robust Python and SQL skills.
Experience deploying ML models into production environments . Experience creating and consuming REST APIs / JSON interfaces . Experience with Git/version control . Positive understanding of ML models, feature engineering, model scoring, and model monitoring.

Preferred Skills Experience with some of the following would be advantageous: AWS Step Functions / Event Bridge Sage Maker Pipelines / Model Registry / Model Monitor Docker / Amazon ECR CI/CD pipelines Terraform / Cloud Formation / AWS CDK Fraud, credit risk, transaction risk, or financial-services models Experience & Qualification 1+ years overall experience preferred Minimum 1 year of direct hands-on AWS experience Bachelor's/Master's degree in Computer Science, Engineering, Data Science, or a related discipline

📌 Data Scientist/ Aws Data Engineer Bengaluru
🏢 Barri Financial Group
📍 Bengaluru