Description
You will develop and deploy machine learning models to predict operational issues using historical data analysis.
Responsibilities
- Develop, test, and validate machine learning models to predict 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.
- Write modular code that passes static and dynamic Info-sec vulnerability scans and document all model runbooks.
- 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.
- Strong data engineering and data analytics capabilities.
- Ability to evaluate models using accuracy, precision, recall, F1-Score, MSE, and R-squared.
- Experience using Azure DevOps for project management.
- Proficiency in Tableau for data visualization.
- Ability to perform testing and validation for both data and developed models.
Preferred Skills
- Experience automating infrastructure and code changes.