Description

Key Responsibilities

• Design and implement end-to-end 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 end to end 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

Key Skills

Education

Any Gradute