Overview
This role supports the development and management of statistically derived credit risk modeling used for loan and deposit originations, account management, collections, loan loss forecasting, capital plans, and stress testing.
The Sr Statistical Modeling Analyst manages statistical model development and implementation independently and in collaboration with stakeholders across the organization.
Pay Range
- Target Pay Range: $128,900.00–$157,500.00 annually
- Full Pay Range: $99,900.00–$186,400.00 annually
Compensation decisions are based on factors such as relevant job-related skills, experience, and education or training. If an offer is made, individual qualifications will be considered. Additional compensation incentives are available and are performance based; targets vary by role.
Benefits
- 401(k) Company Match (up to 3%)
- 4% annual contribution to your 401(k)
- Medical, Dental and Vision (family contributions as well)
- PTO Program + Exchange Program
- Tuition Reimbursement Program
- Volunteer time off + donation match
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)
- Exposure at Default (EAD)
- Apply these models to credit decision scorecards, 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 model suites to improve accuracy (PD, LGD, EAD, and loan loss forecast models)
- Collaborate with business partners and product management to interpret model results, assess appropriateness of statistical methods and models, and generate actionable insights
- Provide value-added solutions to enhance risk-return trade-off using advanced analytical packages
- Participate in annual model reviews and performance testing
- Manage the data request and systems testing process, including gathering and evaluating data reliability/usability and researching/applying data treatment methods
- Work with senior team members across the advanced credit risk models development lifecycle
- Participate in team meetings related to statistical model development
- Deliver regular reports of modeling results, including impacts of originations, servicing, collection, loss mitigation, and asset liquidation strategies and performance
- Maintain strong understanding of loan portfolio trends and composition while analyzing and presenting model outputs
- Use data warehouse information and model results to support credit risk management strategies
- Identify opportunities to improve efficiency and effectiveness, including reporting requirements
- Develop and maintain statistical modeling documentation and change control documentation
- Perform other duties as assigned
Requirements
- 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
- 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 PD, EAD, and 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
- Excellent analytical and problem-solving skills required
- Ability to interact with management officials at all levels and other risk and model management personnel throughout the organization required
- Ability to analyze and reconcile large volumes of data so it can be summarized and used for management decisions required
Preferred Qualifications
- Experience with statistical modeling for capital planning and stress testing
- Experience with Comprehensive Capital Analysis Review (CCAR), Dodd-Frank Act Stress Testing (DFAST), and Basel Regulatory Capital Framework
- Experience with modeling techniques including logistic regression, multivariate analysis, and Monte Carlo
- Experience communicating complex statistical insights and implications in verbal and written form to support credit union strategy and value creation
Equal Employment Opportunity
The employer 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.