Senior Credit Risk Modeling Lead

BECU; Arizona; On-site; USD 129,000 - 158,000; Full time

Benefits offered by this job

401(k) Company Match

Medical, Dental and Vision

PTO + Exchange Program

Tuition Reimbursement

BECU Cares volunteer time off + donor匹

Job summary

BECU is seeking a Sr Statistical Modeling Analyst to develop and manage statistically derived credit risk models used in loan originations, account management, and loss forecasting. You will lead model development independently and with stakeholders across the credit union.

Ideal candidates have a Master’s in a quantitative field and 3+ years in credit risk modeling, with proficiency in SAS, Python, SQL, and R, plus knowledge of CCAR/DFAST and Basel frameworks.

Qualifications

• Master’s degree or foreign equivalent in a quantitative discipline such as statistics, math, finance, or economics required.
• Minimum 3 years of functional experience in statistical modeling required including credit risk modeling in mortgage, auto, credit card, or business loan products.
• Knowledge of logistic regression, survival analysis, Markov chain analysis and time series methodologies.
• Knowledge of AI and ML tools; proficiency in SAS, Python, SQL and R.
• Experience with capital planning, CCAR, DFAST, Basel frameworks preferred.

Responsibilities

• Develop, re-develop, and calibrate statistical models (PD, LGD, EAD) for credit decision scorecards and forecasts.
• Collaborate with business partners to interpret model results and support business decisions.
• Participate in annual model reviews and performance testing.
• Manage data requests and testing; ensure data reliability and proper treatment methods.
• Document modeling processes and change control.

Skills

Statistical modeling

Credit risk modeling

Analytical thinking

Communication

Education

Master's degree in quantitative field

Tools

SAS

Python

SQL

R

Job description

BECU is seeking a Sr Statistical Modeling Analyst to develop and manage statistically derived credit risk models used in loan originations, account management, and loss forecasting. You will lead model development independently and with stakeholders across the credit union.

Ideal candidates have a Master’s in a quantitative field and 3+ years in credit risk modeling, with proficiency in SAS, Python, SQL, and R, plus knowledge of CCAR/DFAST and Basel frameworks.