Loss Forecasting & Performance Analytics Manager, Earnest

• 6+ years of experience in risk modeling, credit performance analysis, or related fields, including developing and maintaining loss forecasting models
• 3+ years of hands-on experience in SQL and Python programming for advanced data analysis and modeling
• Strong expertise in statistical modeling, loss forecasting methodologies, and sophisticated risk data analysis
• Experience with BI/reporting tools such as Looker or Tableau
• Proficiency in Microsoft Office (Excel, PowerPoint) or Google Suite (Sheets, Slides)
• Excellent verbal and written communication skills, with the ability to present complex findings clearly to both technical and non-technical audiences
• Demonstrated ability to manage multiple priorities and projects under tight deadlines while mentoring and guiding team members
• Knowledge of consumer lending products, financial modeling, and P&L evaluation
• Willingness to travel to the Oakland office monthly to collaborate with other Earnies

Desirable

• The Loss Forecasting & Performance Analytics Manager will report to the Head of Risk
• Lead the development, maintenance, and monitoring of loss forecasting models across Earnest’s loan portfolios (e.g., Student Loan Refinance, Private Student Loan, Personal Loan)
• Analyze portfolio performance, providing data-driven insights and actionable recommendations to improve risk and profitability
• Collaborate with teams across credit strategy, finance, and capital markets to strengthen loss forecasting and analytics processes
• Set the technical direction for loss forecasting and performance analytics by proposing methodologies, tools, and technologies to drive portfolio insights and decision-making
• Develop and maintain loss forecasting models incorporating macroeconomic conditions and other relevant factors to establish forward-looking views of performance and risks
• Analyze and present portfolio performance metrics such as life-of-loan losses, ROE sensitivity, and variance between actual and forecasted outcomes to senior executives and external stakeholders
• Build and enhance robust data pipelines and governance processes to ensure data accuracy, quality, and reliability
• Create executive-ready materials for performance insights, rating agency updates, and financing due diligence
• Drive innovation in tools, methodologies, and data use to improve risk and portfolio analysis
• Manage multiple projects and stakeholders, ensuring timely execution