Model Validation

Education: Bachelor’s or Master’s degree in statistics, mathematics, economics, finance, data science, or a related quantitative field.
Experience: 3+ years in model validation or MRM governance within a regulated financial institution or consulting firm with consumer lending or credit card experience and banking experience preferred. Exposure to AI implementation and/or Governance
Technical skills: SQL and Python required, AWS/Sagemaker AI experience preferred and good to haves are SAS or R
Model Types: Experience with credit risk, underwriting, pre-screen, fraud, marketing or other banking models, including statistical (i.e. regression and time series) and machine-learning models.
Governance: Experience with model inventory, risk-tiering, validation schedules, findings management, approvals, Ongoing Monitoring and Model Governance requirements.
Reporting: Ability to write clear validation reports and present results to management, auditors, regulators, and bank partners
Validation and Model Monitoring: Experience evaluating model performance and model drift using metrics such as AUC, KS, capture rate, PSI, back-testing, benchmarking, stability analysis, and outcome/bad-rate trends
Independent Challenge: Ability to critically evaluate model assumptions, methodology, results, and developer conclusions

Work arrangement
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