Analyze large, complex datasets to extract meaningful insights and identify trends, and develop, train, and evaluate machine learning models using AWS services.
Requirements
- AWS data processing tools
- AWS services such as SageMaker
- TensorFlow
- AWS Glue
- Redshift
- Textract
- SageMaker and Lambda
Responsibilities
- Analyze large, complex datasets to extract meaningful insights and identify trends.
- Perform exploratory data analysis (EDA) using AWS data processing tools.
- Build, train, and evaluate machine learning models using AWS services such as SageMaker, and frameworks like TensorFlow.
- Work with AWS Glue, Redshift, Textract and other data engineering tools to preprocess, transform, and manage data for machine learning purposes.
- Develop end-to-end machine learning pipelines on AWS to automate and operationalize the deployment of models at scale.
- Deploy models to production and set up monitoring systems to track performance, accuracy, and other key metrics.
- Use SageMaker and Lambda for model hosting and API development.
Other
- Work closely with data engineers, business analysts, and stakeholders to understand business needs and tailor data science solutions to meet those needs.
- Document models, processes, and findings for stakeholders, enabling clear communication of results and decision support.
- Discretionary Annual Incentive.
- Comprehensive Medical Coverage: Medical & Health, Dental & Vision, Disability Planning & Insurance, Pet Insurance Plans.
- Family Support: Maternal & Parental Leaves.
