Offer summary

Qualifications:

Master's or PhD in a quantitative field such as Statistics, Mathematics, Data Science, or Engineering., 8-10 years of experience in model validation within the financial services industry, especially with FCRA-regulated data., Expertise in credit scorecard, survival models, and familiarity with macroeconomic and CECL models., Strong programming skills in SQL, R, and Python, with experience in cloud platforms like Azure and Databricks..

Key responsibilities:

Conduct technical reviews of models and identify areas for improvement.

Develop and maintain the model inventory and risk dashboards.

Present validation results and risk assessments to stakeholders and regulators.

Lead evaluation of vendor solutions and stay updated on industry best practices.

Job description

Who You Are

You are an experienced and motivated Senior Director of Model Validation who is passionate about model risk management innovations. Beyond ensuring compliance, you will drive innovations that enhance corporate-wide model efficiency and deliver measurable business results. This position provides the opportunity to shape and elevate model validation into a strategic, value-added function that integrates technical insights, business intuition, and cutting-edge industry practices. Your work will be highly visible to senior management and key stakeholders.

What You'll Do

The Senior Director of Model Validation will conduct comprehensive technical reviews of individual models, including formulating questions, engaging stakeholders, performing technical analyses, and identifying areas for improvement.

The Senior Director of Model Validation will develop and maintain the model inventory, ensuring its accuracy and relevance, and design an aggregated model risk dashboard to provide a holistic view of the organization’s model risk landscape.

Present individual validation results and aggregated model risk assessments to stakeholders, senior management, and regulators, articulating both technical insights and actionable recommendations.

Lead the evaluation and integration of modern vendor solutions to enhance model risk management practices and support overall efficiency improvements.

Stay abreast of industry best practices, regulatory expectations, and emerging trends, including advancements in AI and machine learning models, and provide cost-efficient recommendations for resource allocation and model roadmaps.

Oversee the assessment and management of AI model risks, ensuring robust validation frameworks are in place to address explainability, fairness, robustness, and governance challenges.

Foster cross-functional collaboration to integrate model validation insights into broader strategic and operational decision-making processes.

What You'll Need

Master’s/PhD degree in Statistics, Mathematics, Data Science, Operations Research, Engineering, or a related quantitative field.

8-10 years of experience in modeling and/or validation within the financial services industry, with a strong emphasis on FCRA-regulated data (e.g., credit bureau attributes).

Extensive expertise in credit scorecard and survival model methodologies, along with familiarity with macroeconomic data and CECL models.

Proven ability to navigate and assess AI model risks, including a deep understanding of fairness, interpretability, robustness, and governance in AI applications.

Strong communication skills, including written, verbal, and data storytelling, with a demonstrated ability to interact effectively with regulators, senior management, and technical teams.

Proficiency in SQL, R, and Python programming, with experience manipulating large datasets.

Hands-on experience with Microsoft Azure, Databricks, and analytics in a cloud environment is highly desirable.

A track record of implementing modern vendor solutions in the model risk space, driving efficiencies, and improving organizational capabilities.

Leadership and team management experience, with a collaborative approach to achieving goals and fostering innovation.

Required profile