Credit Model Governance Lead

Plaid; San Francisco (CA); Sur place; USD 180 000 - 240 000; Plein temps

Avantages offerts par ce poste

Equity

Bonuses/Commissions

Résumé du poste

Plaid seeks a Model Governance Lead, Credit to own the governance framework for its Credit Score and Insights products. You will validate models, ensure documentation, and advise on risks and improvements, working with cross-functional teams to strengthen model governance.

The role emphasizes independence, rigorous validation, and responsible use of ML in credit scoring, with collaboration across Product, Data Science, and Engineering.

Qualifications

• 7+ years of experience building and owning a model governance program.
• Experience in model validation, model risk management, model development, or Data Science.
• Deep knowledge of models built for credit purposes.
• Strong understanding of machine learning concepts and defensible validation.
• Familiarity with foundation models and neural networks.
• Experience assessing data inputs, model performance, and use-cases.
• Independent, detail-oriented, and curious mindset.

Responsabilités

• Own and execute Plaid’s Model Governance program for Credit products.
• Assess conceptual soundness, data, features, performance, and intended use of credit models.
• Identify weaknesses and translate into remediation plans.
• Partner with Product, Data Science, and Engineering to strengthen governance practices.
• Create clear, rigorous documentation for customers to understand models.

Connaissances

Model governance

Credit modeling

Model validation

Data science

Independent thinker

Challenging stakeholders

FinTech experience

Outils

XGBoost

Description du poste

Plaid seeks a Model Governance Lead, Credit to own the governance framework for its Credit Score and Insights products. You will validate models, ensure documentation, and advise on risks and improvements, working with cross-functional teams to strengthen model governance.

The role emphasizes independence, rigorous validation, and responsible use of ML in credit scoring, with collaboration across Product, Data Science, and Engineering.