Data Scientist

• Develop, validate, and maintain predictive credit risk models for credit origination, behavioral risk, portfolio management, and other risk use cases
• Own the full modeling lifecycle, including problem definition, population and target construction, feature engineering, development, validation, backtesting, calibration, monitoring, and recalibration
• Use SQL and Python to explore large datasets, identify portfolio trends, analyze delinquency and losses, and develop actionable risk strategies
• Support underwriting strategies, score cutoffs, credit limits, segmentation, and portfolio management policies
• Build monitoring frameworks for model discrimination, calibration, stability, data drift, portfolio trends, vintages, roll rates, delinquency, and other risk indicators
• Validate data sources, implement data quality controls, assess feature stability, and identify leakage, selection bias, and population drift
• Contribute to methodologies addressing reject inference, selection bias, thin-file populations, and limited performance information
• Use Databricks, MLflow, GitHub, Python, SQL, scikit-learn, and other modeling tools to build reproducible, documented analytical solutions
• Collaborate with Data and Engineering teams to deploy and integrate models into business decision flows
• Communicate analytical findings to Risk leadership and non-technical stakeholders and translate model outputs into business strategies
• Build scalable risk analytics methodologies across Mexico, Brazil, and Colombia

Data Scientist jobs in Colombia

Senior Data Scientist – Risk Modeling