Modeling Analytics - Associate

As a professional within the Consumer Credit Forecasting team, you will have the opportunity to contribute to the execution of credit loss forecasting models, diagnose model accuracy, and lead analyses to assess relationships and patterns promoting loss performance of the product portfolio. Additionally, you will spearhead the control framework within the function, leveraging analytical insights, predictive analysis, and newer technology applications. You may also engage in process reengineering efforts to streamline and automate redundant activities in a fast-paced environment. - Execute credit loss forecasting models for forecasting credit losses and allowance for the product portfolio supporting regulatory exercises like CCAR, CECL, Firmwide Risk Appetite, and Budget - Present loss forecasting results and levers to senior management and internal stakeholders - Diagnose model parameters and collaborate with the modeling team to propose changes for accuracy at granular segments - Participate in cross-functional communications with Risk Management, Finance, Marketing, and Collections to inform forecasts and incorporate strategic initiatives - Conduct macro sensitivity analytics, loss and allowance attribution, deep dives, and storyboarding - Lead advanced analyses to assess relationships and patterns driving loss performance - Maintain key control evidence integrity by securely documenting and copying control artifacts to the designated controls path - Coordinate with stakeholders to ensure timely validation and communication of results - Bachelor's or Master's Degree in a quantitative discipline (Finance/Stats/Econ/Math/Engineering) or equivalent work/training - Minimum of 3 years of Credit Risk Management, product/revenue analytics, and/or consulting experience - Strong knowledge of Python/SQL/Tableau/SAS/Alteryx/Cloud application architecture - Proficiency in Microsoft Office suite of products (Advanced Excel, VBA, and PowerPoint) - Strong analytical and problem-solving skills with the ability to interpret large amounts of data and its impact in operational or financial areas - Well-organized and structured with strong communication and presentation skills,