SUPERVISORY RESPONSIBILITY
None
*ESSENTIAL JOB FUNCTIONS
• Build and maintain complex underwriting models for private student loan and other unsecured consumer loan products, from scoping requirements, data preparation and cleansing, variable reduction, to parameter estimation and model performance assessment
• Assist in implementing underwriting and performance models into in-house and third-party decisioning engines
• Develop supporting processes for cash flow modeling, performance monitoring, and loss tracking
• Present reports regarding credit loss estimates and impact of credit policy and business development on credit profiles to Credit Risk Committee
• Work with other analysts and data engineers on quality assurance of source data and systems, analyses, and reporting
• Evaluate alternative data sources for use in predictive models
• Create and maintain documentation of credit risk models for dissemination by our internal and external partners as well as regulators
• Collaborate with other departments on developing predictive models across the complete value chain of unsecured lending products (marketing, operations, collections)
OTHER DUTIES AND RESPONSIBILITIES
• Other duties and responsibilities as assigned to support operational and analytical needs in the areas of Credit Risk, Portfolio Management, and Finance
QUALIFICATIONS
Preparation, Knowledge, Previous Experience:
• At least 4 years of experience as an analyst in the consumer lending space (mortgages, HELOCs, auto, cards, other revolvers, unsecured), preferably with student loan experience
• At least 2 years of experience in a quantitative role working on credit risk models, preferably with student loans or other unsecured loans
• Preferred experience in reviewing and implementing credit risk models and strategies
• Preferred experience utilizing data from the major consumer reporting agencies (Equifax, Experian, TransUnion)
• Proven track record of building models in either SAS (Base SAS, SAS EG) or R
• Statistical Programming Knowledge (SAS, R, Python, SQL, etc.) advantageous
• Experience in statistical techniques, risk classification algorithms, credit risk scoring, model validation techniques and metrics
Skills, Abilities, Competencies:
• Excellent inter-personal and communications skills with both peers and senior executives
• Track record of continuing education via webinars, conference attendance, or local support group involvement
• Highly organized self-starter who can own projects and act with limited supervision
• Ability to remain focused in a fast paced, “open office” environment
• Collaborative team player, eager to learn from and share knowledge with colleagues
Level of Education Required:
• Prefer bachelor’s degree in a quantitative discipline (Mathematics, Economics, Information Technology, Engineering, Science), Business, or equivalent working experience; Master’s Degree or PhD preferred
WORKING CONDITIONS & PHYSICAL DEMANDS
Office environment working with personal computer for extended periods of time.
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