Director, Credit Risk (CECL Modeling)

Navy Federal Credit Union•Vienna, VA

1d•Onsite

About The Position

Leads the development and deployment of Navy Federal Credit Union Lending CECL and credit risk predictive models, post-model adjustments, advanced analytics, and statistical solutions that deliver actionable business insights. Develops strategic priorities and analytical approaches, ensures model quality and performance, and aligns work with corporate initiatives and goals. Manages the daily activities of professional employees under limited supervision. The role leads end-to-end CECL model development, implementation, execution, monitoring, documentation, and governance for consumer lending portfolios. It oversees credit risk policies and performance, advises senior and executive leadership on credit and financial insights, and helps shape lending and portfolio-management strategies. The director also leads analytics integration—including machine learning and AI techniques—and collaborates with stakeholders to develop risk mitigation strategies and support sustainable growth of Navy Federal’s lending products. This position is located at 820 Follin Lane, Vienna, Virginia. Hours are Monday through Friday, 8:00 a.m. to 4:30 p.m. Applicants must be authorized to work in the United States without current or future sponsorship.

Requirements

College or university degree and 10–15+ years of work experience in credit risk assessments at a large financial institution.
At least 6 years of management experience.
Expert knowledge of underwriting and credit risk processes and the interactions between consumer behavior and the macroeconomic environment.
Expert knowledge of applicable federal and state laws, rules, and regulations.
Expert knowledge of banking and financial industry trends, products, and services.
Expert knowledge of debit and/or credit card fraud issues, patterns, and processes.
Extensive experience developing strategy and conducting in-depth analytics in consumer lending across the credit lifecycle.
Expert thought leadership, initiative, decision-making, and creativity in solving business problems.
Experience managing multiple priorities independently and/or in a team environment to achieve goals.
Expert knowledge of methodologies used to measure, model, and simulate credit risk, regulatory risk, and risk exposure in relevant lending products.
Advanced experience analyzing data to identify operational credit risk red flags.
Advanced ability to influence and build consensus with business partners, provide credible challenge diplomatically, and drive strategic outcomes.
Broad experience working with staff, management, stakeholders, and vendors at all levels.
Leadership expertise managing credit risk teams in high-stakes, high-volume environments.
Advanced data analytics and programming skills, including SQL, R, Python, Hadoop, SAS, SPSS, Scala, and AWS.

Nice To Haves

Advanced degree (Master’s or Ph.D.) in a quantitative discipline or related field, or equivalent combination of training, education, and experience.
Advanced knowledge of Navy Federal’s functions, philosophy, operations, and organizational objectives.
Advanced knowledge of CECL reserving, credit loss forecasting, and Model Risk Management guidelines.
Extensive experience with consumer lending portfolios such as credit card, auto, secured or unsecured consumer lending, mortgage, or home equity.
Expertise in loan- or account-level credit loss modeling techniques, including probability of default, loss given default, exposure at default, prepayment, survival/hazard, and competing risk models.
Expertise implementing controlled model production processes, including version control, data validation, reconciliation, monitoring, documentation, and change management.
Experience responding to Model Risk Management validation, internal audit, external audit, regulatory, accounting, or control review questions.
Advanced knowledge of applicable laws and regulations governing credit cards and secured and unsecured consumer lending.
Advanced knowledge of financial industry trends, products, services, credit cycles, portfolio performance drivers, and reserve implications.
Extensive experience leading and managing an analytics or quantitative modeling operation in a large financial institution, including operational, regulatory, model risk, and control considerations.
Expert research, data-mining/querying, analysis, and reporting skills, including sophisticated statistical methods, modeling, forecasting, and cost/benefit/risk analysis.
Extensive experience demonstrating thought leadership, sound judgment, decision-making, and creativity in solving business problems.
Extensive experience working with staff, management, stakeholders, vendors, control partners, and executive audiences at all levels.
Expert skill presenting findings, conclusions, alternatives, model limitations, and recommendations clearly and concisely to varied stakeholders.
Expert ability to influence, negotiate, and persuade to reach agreement and positive outcomes.

Responsibilities

Manage, lead, and mentor teams of data scientists and analysts developing statistical models, algorithms, and data-mining techniques to address business problems and support business initiatives.
Lead end-to-end CECL model development, implementation, execution, monitoring, documentation, and governance for consumer lending portfolios.
Oversee development of credit risk policies aligned with regulatory requirements, industry best practices, and organizational financial and strategic goals.
Communicate credit and financial insights to senior leadership and advise on credit risk strategies and lending decisions based on trends, risks, and market conditions.
Present analytical models and strategic insights to the executive team to influence portfolio-management and credit risk strategy decisions.
Monitor and report on credit risk performance relative to financial objectives and corporate risk appetite, and recommend improvements.
Ensure effective credit risk management by applying analytical techniques, financial modeling, and forecasting tools.
Lead integration of new data sources and analytics into credit risk management, including machine learning and AI techniques for credit assessments and financial predictions.
Collaborate with, advise, and counsel stakeholders on complex credit risk issues and guide business units throughout credit risk lifecycles.
Collaborate with senior leadership to design risk mitigation strategies and business intelligence supporting sustainable growth of lending products.
Supervise and mentor the credit risk team, providing guidance on credit risk analysis and financial performance assessments and developing team capabilities.