JOB DESCRIPTION:
Design and implement endtoend machine learning ML pipelines using services such as Amazon SageMaker AWS Glue AWS Lambda and Amazon S3
Perform data collection cleaning and feature engineering to prepare datasets for modeling
Develop predictive models and statistical analyses using Python R or similar tools
Deploy monitor and optimize ML models in production environments using AWS ML Ops best practices
Collaborate with data engineers to design ETL pipelines and ensure data availability and reliability
Utilize AWS analytics services Athena Redshift QuickSight EMR for advanced reporting and visualization
Work with stakeholders to translate business objectives into data science solutions and actionable insights
Apply AIML algorithms for use cases such as forecasting anomaly detection NLP computer vision and recommendation systems
Maintain compliance with security and governance standards for data management on AWSKey Responsibilities
Design and implement endtoend machine learning ML pipelines using services such as Amazon SageMaker AWS Glue AWS Lambda and Amazon S3
Perform data collection cleaning and feature engineering to prepare datasets for modeling
Develop predictive models and statistical analyses using Python R or similar tools
Deploy monitor and optimize ML models in production environments using AWS ML Ops best practices
Collaborate with data engineers to design ETL pipelines and ensure data availability and reliability
Utilize AWS analytics services Athena Redshift QuickSight EMR for advanced reporting and visualization
Work with stakeholders to translate business objectives into data science solutions and actionable insights
Apply AIML algorithms for use cases such as forecasting anomaly detection NLP computer vision and recommendation systems
Maintain compliance with security and governance standards for data management on AWS"
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