Statistical Modeling Manager

BECU

4d•Hybrid

About The Position

As a Statistical Modeling Manager at BECU, you’ll be at the forefront of data-driven decision-making that directly supports the financial well-being of our members. You’ll lead the development and oversight of advanced credit risk models that shape how we approach Economic Capital, loan loss forecasting, account management, collections, capital planning, and stress testing. Your deep understanding of statistical theory and hands-on experience with large datasets will help BECU build stronger, smarter, and more resilient credit strategies. You’ll influence key business decisions while partnering across teams to ensure that every model you manage translates into actionable insights. Here, your expertise won’t just power risk strategies—it will strengthen the financial future of the people and communities we serve. To join our dynamic team in this role, we require candidates to be residents of WA, OR, ID, CA, AZ, TX, GA, SC, NC, and VA. If you’re located in Washington state and within a reasonable driving distance to our Tukwila Headquarters (TFC), we encourage you come into the office on Tuesdays & Wednesdays each week. For those candidates that live outside the commutable distance to TFC and in any of our approved remote work locations, this role will be primarily remote. Remote or onsite, we are committed to ensuring you are fully engaged and included in our collaborative environment.

Requirements

Master’s degree or foreign equivalent in a quantitative discipline such as statistics, math, finance, or economics.
Minimum 7 years of functional experience in credit risk modeling.

Nice To Haves

Sound knowledge of statistical modeling concepts including logistic regression, survival analysis, Markov chain analysis and time series.
Knowledge of artificial intelligence (AI) and machine learning (ML) tools.
Knowledge of three or more of the following statistical analytical packages: SAS, Python, SQL and R.
Experience in verbal and written communication of complex statistical insights.
Experience with loss forecasting, default management and credit risk modeling, reporting and analytics.
Experience with Basel Regulatory framework, Comprehensive Capital Analysis Review (CCAR), Dodd-Frank Act Stress Testing (DFAST).
Credit Risk modeling experience in real estate secured loan products (i.e., mortgage, home equity), auto, credit card, Consumer and/or commercial loan products.

Responsibilities

Lead Model Development: Design, develop, and recalibrate statistical credit risk models—ranging from credit decision scorecards to Basel IRB models like PD, LGD, and EAD—using leading statistical software and programming tools.
Champion Data Integrity: Gather, validate, and refine large datasets to ensure models are built on reliable, usable data—and apply advanced treatment techniques where needed.
Implement with Precision: Manage systems testing and data readiness to support accurate and efficient model implementation.
Evaluate and Enhance Models: Conduct ongoing performance assessments and annual reviews to identify enhancements and improve model accuracy using cutting-edge statistical methods.
Drive Business Alignment: Partner with business and product teams to explain model outcomes, guide risk-reward strategies, and ensure alignment between statistical insights and business objectives.
Maximize Analytic Impact: Provide advanced analytics in support of credit risk strategy, including capital planning, portfolio mix management, and loss forecasting—applying tools like SAS, SQL, and other statistical platforms.
Standardize Model Governance: Develop and maintain risk modeling procedures and documentation to support consistency, auditability, and stakeholder transparency.
Translate Insights: Present model results and recommendations clearly to both technical and non-technical stakeholders, supporting enterprise-wide understanding and action.
Stay Ahead of the Curve: Maintain up-to-date knowledge of credit portfolios, regulatory requirements, and industry trends to drive continuous improvement in modeling practices.
Deliver Cross-Functional Support: Respond to data requests, manage testing environments, and ensure model outputs are leveraged effectively across teams.
Ensure Thorough Documentation: Maintain detailed records, including model development logs, version controls, and validation documentation for regulatory and business needs.
Contribute Beyond the Role: Take on additional responsibilities and special projects that support BECU’s mission and modeling excellence.