Sr Statistical Modeling Analyst

BECU; Idaho; On-site; USD 100,000 - 186,000; Full time

Benefits offered by this job

401(k) Company Match

4% 401(k) annual contribution by BECU

Medical, Dental and Vision

Job summary

BECU is seeking a Sr Statistical Modeling Analyst to lead development and management of credit risk models used for loan origination, servicing, and capital planning. The role collaborates with stakeholders to ensure robust model performance and regulatory alignment.

The candidate will calibrate models, validate performance, and produce reports showing impacts across originations, collections, and asset strategies. Advanced analytics and data-driven decision support are central to this role.

Qualifications

• Master’s degree in a quantitative field is required.
• Minimum 3 years of statistical modeling experience including credit risk.
• Knowledge of PD, LGD, EAD modeling and survival/time series methods.
• Experience with AI/ML tools and data analysis.
• Strong communication and ability to summarize complex insights.

Responsibilities

• Develop, calibrate, and validate statistical models for credit risk.
• Research enhancements to improve PD/LGD/EAD models.
• Communicate model results to stakeholders and support risk decisions.
• Participate in model reviews, testing, and documentation.
• Manage data requests and data quality considerations.
• Prepare reports on originations, collections, and capital planning.

Skills

Analytical thinking

Communication skills

Team collaboration

Verbal and written communication

Education

Master’s degree in statistics, math, finance, or economics

Statistics coursework at bachelor/master/PhD level

Tools

SAS

Python

SQL

R

Job description

Is it surprising to hear that a financial institution of 1.5 million members and over $30 billion in managed assets say that success comes from focusing on people, not profits? Our “people helping people” philosophy has guided us since 1935, driving our deep commitment to serving our members, communities, and each other. When you join our team, you become part of a purpose-driven organization where your work makes a real difference. While we’re proud of our history, we’re even more excited about our future. With business and technology transformation on the horizon, there’s never been a better time to be part of BECU. You bring more than your expertise to your role, and that matters here. Your story, perspectives, and lived experiences help shape belonging at BECU and deepen how we connect with and support our employees, our members, and our communities.

PAY RANGE

The Target Pay Range for this position is $128,900.00-$157,500.00 annually. The full Pay Range is $99,900.00 - $186,400.00 annually. At BECU, compensation decisions are determined using factors such as relevant job-related skills, experience, and education or training. Should an offer for employment be made, we will consider individual qualifications. In addition to your salary, compensation incentives are available for the hired applicant. Incentives are performance based and targets vary by role.

BENEFITS – Because People Helping People Starts With Supporting You

• 401(k) Company Match (up to 3%)
• 4% annual contribution to your 401(k) by BECU
• Medical, Dental and Vision (family contributions as well)
• PTO Program + Exchange Program
• Tuition Reimbursement Program
• BECU Cares volunteer time off + donation match

Summary

The Sr Statistical Modeling Analyst is responsible for the development and management of statistically derived credit risk modeling used by the credit union for loan or deposit originations, account management, collections, loan loss forecasting, capital plans and stress testing. The Sr Statistical Modeling Analyst will manage statistical model development and implementation independently and through collaboration with stakeholders throughout the credit union.

Responsibilities

• Develop, re-develop, and calibrate statistical models using statistical analytical packages; including but not limited to: Probability of Default (PD), Loss Given Default (LGD), and Exposure at Default (EAD) models for credit decision scorecard, loss forecasting, reserving, and economic capital use cases. Support documentation and execution of statistical models under the direction of senior level peers and leadership.
• Research and apply enhancements to existing suite of models to improve accuracy, partnering with senior level peers and leadership. Research statistical methods and apply enhancements to existing suite of models to improve accuracy. Scope includes Probability of Default (PD), Loss Given Default (LGD), Exposure at Default (EAD), and loan loss forecast models.
• Collaborate with business partners and product management to help interpret model results and assess the appropriateness of statistical methods and models for addressing business questions and generating actionable insights. Provide value-added solutions for the enhancement of risk-return trade-off through the application of advanced analytical packages.
• Participate in annual model reviews and performance testing.
• Manage the data request and systems testing process. Gather and evaluate data for reliability and usability and research and apply data treatment methods.
• Work with senior members of the team on all aspects of the advanced credit risk models development life cycle.
• Participate in team meetings related to statistical model development.
• Deliver regular reports of modeling results to include impacts of originations, servicing, collection, loss mitigation and asset liquidation strategies and performance.
• Maintain a thorough knowledge relating to loan portfolio trends and composition, while analyzing and presenting model outputs.
• Utilize data warehouse information, along with model results, to assist in the development of credit risk management credit risk strategies.
• Identify opportunities for efficiency and effectiveness, including reporting requirements.
• Develop and maintain statistical modeling documentation and change control documentation.
• Perform other duties as assigned.

Qualifications

• Master’s degree or foreign equivalent in a quantitative discipline such as statistics, math, finance, or economics required. Coursework in statistics at either the bachelor’s, master’s or PhD level required.
• Minimum 3 years of functional experience in statistical modeling required including credit risk modeling experience in one or more of the following product areas: real estate secured loan products (mortgage, home equity), auto, credit card or commercial loan products.
• Sound knowledge of statistical modeling concepts, including logistic regression, survival analysis, Markov chain analysis and time series methodologies, with experience developing and validating Probability of Default (PD), Exposure at Default (EAD), and Loss Given Default (LGD) models required.
• Knowledge of artificial intelligence (AI) and machine learning (ML) tools required.
• Knowledge of three or more of the following statistical analytical packages required: SAS, Python, SQL and R.
• Experience with statistical modeling for capital planning and stress testing preferred.
• Experience with Comprehensive Capital Analysis Review (CCAR), Dodd-Frank Act Stress Testing (DFAST) and Basel Regulatory Capital Framework preferred.
• Experience with modelling techniques including logistic regression, multivariate analysis, and Monte Carlo preferred.
• Excellent analytical and problem-solving skills required.
• Experience in verbal and written communication of complex statistical insights and implications to Credit Union strategy and value creation preferred.
• Ability to interact with management officials at all levels, as well as other risk and model management personnel throughout the Credit Union required.
• Ability to analyze and reconcile large volume of data so that it can be summarized and eventually used for management decisions required.

EEO Statement

BECU is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, veteran status, disability, sexual orientation, gender identity, or any other protected status.