Credit Data Analyst (Mid-Level)

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