Lead Data Scientist - AWS Sagemaker Engineer

Lead AWS SagemakerOnsite Cincinnati, OHDuration: 12 Months +AWS Sagemaker to expand Feature Store, introduce Model Registry, CI/CD, Real-Time models for our large data science credit models.The squad is currently working on an in-house build of Feature Store to help speed up modeling process for our Data Science department. Combination of Snowflake, Cloud Pak for Data. (More on this later)Currently, data scientist build model features (attributes) about customers in their own Jupyter notebook that feed into their models and never reuseable for others… aka reason for Feature StoreThey are also working on building real time scoring framework for our loan/card application process. Right now it’s batch and can be almost 31 days behind.Technology used: Docker, Kafka, Snowflake, Feature StoreThis is the most important part: They are working on bringing in AWS Sagemaker as a replacement for IBM Cloud Pak for Data. This is where we deploy our critical production models and where all most of modeling is done at the bank.We need someone that has been through standing up AWS Sagemaker into their company and/or someone that can deploy models in AWS Sagemaker.We are in early innings with Sagemaker and just scratching the surface. We need help getting this platform stood up