This role involves designing applied research methods, developing statistical models, and simulating outcomes to evaluate the impact of chronic disease prevention interventions, particularly for the National Diabetes Prevention Program (National DPP). Key tasks include conducting advanced data modeling, managing large datasets using SAS and SQL, and creating compelling visualizations for stakeholders.

The role involves analyzing credit risk exposure, collaborating with various teams to enhance risk metrics, and developing machine learning models for credit and fraud risk assessment. The Data Scientist will also partner with Product and Finance teams to streamline monitoring processes and contribute to the overall credit risk strategy and portfolio management.

The Data Scientist III oversees data management and integration efforts across university, state, and federal agencies, developing processes for ETL into common data repositories. This role also involves coordinating database activities and providing guidance or oversight to other Data Scientists.

The Data Scientist will develop and optimize predictive and prescriptive models, applying deep learning and neural networks for customer classification and personalization. This role involves utilizing MLOps and GCP services to deploy and maintain ML models, alongside implementing LLMs and Generative AI solutions.