Description

You will develop and deploy machine learning models to predict operational issues using historical data analysis.

This role is on-site.

Responsibilities

• Develop, test, and validate machine learning models to forecast future operational issues.
• Build data models and engineering pipelines using AWS services including SageMaker, Glue, Lambda, S3, and Redshift.
• Analyze trends and bottlenecks within the MR0 process and part supply chain.
• Configure monitoring, logging, and alerting mechanisms using CloudWatch and SNS.
• Automate deployments, certificate updates, infrastructure changes, and failure notifications.

Required Skills

• 6+ years of experience in data science or related fields.
• Proficiency in AI/ML modeling and data modeling.
• Experience with AWS SageMaker, Glue, Lambda, S3, and Redshift.
• Hands-on experience with CloudWatch and SNS for monitoring.
• Ability to evaluate models using accuracy, precision, recall, F1-Score, MSE, and R-squared.
• Strong data engineering and data analytics capabilities.
• Proficiency in Tableau for data visualization.
• Experience using Azure DevOps for project management.
• Ability to perform testing and validation for both data and developed models.

Preferred Skills

• Experience automating infrastructure and code changes.

Key Skills

Education

Any Gradute