Data Scientist, Model Governance

Build out our foundational processes for generating and surfacing model performance metrics, including crafting + calculating the metrics and building python rails. Act as point of contact for Strategic Financial Partners and manage their model governance needs. Regularly conduct performance and exploratory analyses to establish the quality of model outcomes. Provide guidance on the appropriate use of our products, respond to inquiries around model development procedures and generate stability analyses. Create automation to detect inconsistencies or issues with the production models that power our fraud detection products. Primarily work with a Python ecosystem, using SQL, SageMaker, S3, Metabase and Git to support.