Data Scientist - Credit (Retros)
Core
Apply quantitative analysis and credit expertise to help lenders make better use of cash flow insights and build credit retrospectives.
Role type
Mid-level IC data scientist (credit risk)
Builds
Credit risk models, cash flow insights, and data pipelines for lenders
Domain
Financial services / Credit risk
Deliverable
production ML models
Required skills
SQL, Python, credit risk modeling, quantitative analysis, data mining, data visualization, ETL processes
Preferred skills
dbt, lending lifecycle optimization, account-level decisioning
Technologies
dbt, SQL, Python
Responsibilities
Analyze Plaid's unique data to identify emerging credit risk signals and build credit retrospectives; Develop metrics, alerts, and dashboards to monitor production ML model performance; Create tailored recommendations for clients based on their data and Plaid's insights; Build and maintain data pipelines including ETL processes; Inform and influence Product and Engineering teams through clear analysis and presentations.
Seniority
Mid-level, hands-on IC
