Sr Statistical Modeling Analyst

BECU; Washington; On-site; USD 129,000 - 186,000; Full time

Benefits offered by this job

401(k) Company Match (up to 3%)

4% annual 401(k) contribution

Medical, Dental and Vision

PTO + Exchange Program

Tuition Reimbursement

Volunteer time off + donation match

Job summary

BECU is seeking a Sr Statistical Modeling Analyst to develop and manage statistically derived credit risk models used for loan originations, servicing, and risk management. The role involves independent model development and collaboration with stakeholders across the credit union.

The candidate will handle PD, LGD, EAD modeling, capital planning and stress testing, with opportunities to influence strategy and risk management through advanced analytics.

Qualifications

• Master’s degree in a quantitative discipline required.
• 3+ years of experience in statistical modeling, including credit risk.
• Experience developing PD, LGD, and EAD models.
• Knowledge of AI/ML concepts and related tools.
• Proficiency in SAS, Python, SQL, or R.
• Experience with CCAR, DFAST, Basel Capital framework preferred.
• Strong ability to communicate complex statistical insights to leadership.

Responsibilities

• Develop, calibrate and validate credit risk models (PD, LGD, EAD) for decisions and forecasting.
• Collaborate with stakeholders to apply models to business questions and drive actionable insights.
• Participate in model reviews and performance testing.
• Own data requests, testing processes, and data quality assessment.

Skills

Statistical modeling

Logistic regression

Multivariate analysis

Time series

Monte Carlo methods

Data interpretation

AI/ML knowledge

Education

Master’s degree in quantitative field

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.