Support and advise the Advanced Analytics team in identifying opportunities and designing solutions for scalable, reliable, and automated data science products. Leverage Enterprise Data Platform tools (e.g., Snowflake, DBT), AWS services (e.g., EC2, Sagemaker, CodeDeploy, SNS), and open sources products (as needed) to build infrastructure and workflows that will support enterprise deployment of machine learning models built in Python and R.
Requirements:
Prior experience deploying machine learning models with AWS.
Familiarity machine learning operations (MLOps) best practices for deployment and monitoring.
Expertise with AWS services supporting data science and analytics (EC2, Lambda, Sagemaker, Glue)
Proficiency in Python and R
Prior experience as a data scientist a plus
Prior experience preferred with currently UA data platform tool-stack a plus (Snowflake, DBT)