Overview – • This is a hands-on, individual contributor role (no direct reports) focused on designing and implementing advanced statistical forecasting and vintage modeling techniques to support finance transformation efforts. The selected candidate will build a proof of concept to demonstrate the business value of predictive modeling. This is a high-impact, build-from-scratch role — ideal for someone who enjoys modeling, coding, and innovating, rather than managing teams. Written examples of impactful models previously built are highly preferred. Qualification & Requirements – • Develop, validate, and deploy statistical and machine learning models for portfolio- and enterprise-level vintage forecasts • Collaborate across finance, risk, strategy, and technology teams • Present complex modeling results to non-technical stakeholders • Ensure compliance with model governance and regulatory standards • Integrate models into business processes and platforms The top 3-5 skills and qualifications required for this role are: • Strong statistical modeling & forecasting experience • Proficient in Python (required) and/or R (highly desired) • Experience in financial services or highly regulated industries • Prior work in a Fortune 250, publicly traded company • Experience building enterprise-level forecasting or vintage models • Model risk management and governance experience Educational Background: Master's or PhD in quantitative field Preferred Qualifications • Cloud modeling environments (AWS, GCP, Azure) • Data visualization tools (Tableau, Power BI) • Familiarity with finance/accounting principles and credit risk