Senior Risk Modeler

Job Summary

A hands-on modeling role building credit risk models across their full lifecycle - from bureau data exploration to production deployment. It combines rigorous statistical work with direct client engagement and platform operationalization, focused on solutions for credit unions and community banks (delivered through Precision CUSO).

Responsibilities

• Construct predictive features from raw bureau tradeline data (Equifax, Experian, TransUnion) rather than pre-packaged scores.
• Handle data-quality challenges, sparse tradelines, and field inconsistencies specific to credit union populations.
• Integrate third-party data providers with bureau tradelines for enriched feature sets.
• Build scorecards and probability-of-default models using logistic regression, WoE binning, and IV analysis.
• Design risk cohorts with appropriate outcome windows and performance periods, plus sub-segmental and challenger models.
• Apply machine learning techniques while maintaining interpretability for regulatory compliance.
• Perform model validation, back-testing, and continuous monitoring.
• Produce clear model documentation, methodology write-ups, and executive summaries; present to stakeholders and third-party validators.
• Configure analytics and deploy solutions within Corridors Decision Management Platform, collaborating with data engineering on operationalization.

Requirements

Technical skills

• Deep expertise with credit bureau raw tradeline data and attributes.
• Mastery of scorecard methodology: logistic regression, WoE binning, IV analysis, Population Stability Index (PSI), and Gini/KS diagnostics.
• Proficiency with ML techniques (gradient boosting, random forests, regularized regression).
• Understanding of Lending Origination Systems, Core Banking Solutions, and bureau/third-party data API integration.
• Experience working with data engineering teams on model deployment.

Experience attributes

• Demonstrated ability managing complex, multi-threaded delivery engagements.
• Self-starter capable of independent progress in ambiguous environments.
• Track record delivering quality work on aggressive timelines.
• Exceptional written and verbal communication, with a consultative approach to stakeholders.

Nice to have

• Understanding of compliance, governance, and regulatory challenges in US credit unions and community banks (NCUA expectations, fair lending, ECOA/Reg B implications).
• Prior exposure to BSA/AML analytics or fraud model development.
• Research-oriented mindset, comfortable with academic and industry literature.

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