Role OverviewWe 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.Key ResponsibilitiesDevelop, package, and deploy ML models using

Amazon SageMaker .Build and manage

real-time SageMaker 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 → SageMaker → ResponseImplement

logging, monitoring, and alerting

using Amazon CloudWatch.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 SkillsMinimum 1 year of hands-on AWS experienceStrong hands-on experience with Amazon SageMaker, AWS Lambda , Amazon API Gateway, Amazon S3, Amazon CloudWatch, AWS IAM, AWS ETL/data-processing pipelines, AWS Glue, AthenaStrong

Python

and

SQL

skills.Experience deploying ML models into

production environments .Experience creating and consuming

REST APIs / JSON interfaces .Experience with

Git/version control .Valuable understanding of ML models, feature engineering, model scoring, and model monitoring.Preferred SkillsExperience with some of the following would be advantageous:AWS Step Functions / Event BridgeSageMaker Pipelines / Model Registry / Model MonitorDocker / Amazon ECRCI/CD pipelinesTerraform / CloudFormation / AWS CDKFraud, credit risk, transaction risk, or financial-services modelsExperience & Qualification1+ years overall experience preferredMinimum 1 year of direct hands-on AWS experienceBachelor's/Master's degree in Computer Science, Engineering, Data Science, or a related discipline

📌 Data Scientist/ AWS Data Engineer (Mumbai)
🏢 Barri Financial Group
📍 Mumbai