Job Description

The Credit Data Analyst is responsible for the ongoing credit performance, risk management and delinquency monitoring of the company’s home improvement loan portfolio. This role contributes heavily to the end-to-end monitoring, analysis, and optimization of loan performance, ensuring that repayment, delinquency, cure rates, and charge-offs remain within the company’s risk appetite and financial targets.

The Credit Data Analyst is a member of the analytical credit risk team focused on development, testing and implementation of new or enhanced strategies to improve future loan portfolio performance.

Watercress Financial is a home improvement lender originating across the United States. Candidates should be comfortable working in a highly entrepreneurial company where smart ideas, fast analysis, and thinking ahead are high-value personal traits.

RESPONSIBILITIES

• Create and maintain monitoring reporting for consumer loan portfolio performance
• Provide analysis and back-testing to minimize delinquency and charge off, while optimizing loan approval, look-to-book rates, and repayment rates.
• Detect emerging credit risk trends in the economy, market or portfolio, and provide strategic recommendation to reduce credit risk or optimize profitability
• Provide transparent, defensible reporting to executive leadership and risk committees
• Create, maintain and enhance: loan loss forecasting, prepayment models, roll rate analysis, transition rate analysis.

QUALIFICATIONS

• 4yr degree Finance, Accounting, Engineering, Actuarial, Com-Sci or other analytical field (Associates Degree with commensurate experience also considered)
• Two or more years in a consumer lending portfolio management, FP&A, risk, data analysis/modeling or similar role
• Confident working independently , detailed oriented
• Strong working knowledge of: credit bureau data, consumer loan portfolio, loan repayment and delinquency behavior

KNOWLEDGE AND SKILLS

• Experience with consumer loan capital markets, FP&A, loan securitization
• MS Excel, Microsoft Power stack (PowerBI, PowerQuery, PowerPivot, PowerAutomate) and SQL
• MLL, boosted/ensemble and/or chat models