Manager, Model Risk

You will play a pivotal role in high-quality model validation to ensure modeling techniques and results are consistent with strategic uses, models are performing as intended, and complying with related Model Risk Management (MRM) policies, standards, procedures, and regulations. Your expertise will be crucial in supporting model validation initiatives related to quantitative analytic modeling within the Synchrony Model Governance and Validation team. Your passion for model validation and modeling techniques will be greatly valued in Synchrony's Risk team. Key Responsibilities: - Conduct full scope model review, annual review, and ongoing monitoring of model performance for both internally and vendor-developed models, particularly in the areas of loss forecast, with effective challenges to identify potential issues. - Evaluate model development data quality, methodology conceptual soundness, accuracy, and conduct model performance testing including back-testing, sensitivity analysis, benchmarking, etc. to timely identify and highlight issues. - Perform proper documentation within expected timeframes to effectively highlight findings for further review/investigation and facilitate informed discussions on key analytics. - Conduct in-depth analysis of large data sets, support the review and maintenance process of relevant models, and model validation documentation. - Communicate technical information verbally and in writing to both technical and business teams effectively. Additionally, write detailed validation documents/reports for management. - Support additional book of work or special projects as required. Required Skills/Knowledge: - Bachelors/master's degree (or foreign equivalent) in Statistics, Mathematics, or Data Science and 2+ years' experience in model development or model validation experience in the retail section of a U.S. financial services or banking; or 4+ years experience in model development/model validation in the retail section of financial services or banking without a Masters degree. - Understanding of quantitative analysis methods or approaches in relation to credit loss models. - Strong programming skills with 2+ years hands-on experience utilizing Python, Spark, SAS, SQL, AWS, Data Lake for statistical analysis, and managing complex or large amounts of data; or 4+ years of relevant experience in lieu of a degree. Desired Skills/Knowledge: - 2+ years of experience in Model Risk Management or model development in the financial services industry including analytic/modeling/quantitative experience and governance. - Knowledge and experience of credit loss models such as Loss forecasting (PD/LGD/EAD. CECL, Roll rate, etc), Stress testing, Allowance. - Ability to apply analytical skills creatively to solve problems. - Sharp focus on accuracy with extreme attention to detail and the ability to make recommendations as opportunities arise. - Self-motivated, prompt action taker when assigned tasks. - Excellent written and oral communication and presentation skills. Additional Company Details (if present): Synchrony offers best-in-class employee benefits and programs that cater to work-life integration and overall well-being. They provide career advancement and upskilling opportunities for all employees to take up leadership roles. Note: The company-related details have been included to provide a broader perspective on the company's culture and benefits, enhancing your understanding of the work environment. You will play a pivotal role in high-quality model validation to ensure modeling techniques and results are consistent with strategic uses, models are performing as intended, and complying with related Model Risk Management (MRM) policies, standards, procedures, and regulations. Your expertise will be crucial in supporting model validation initiatives related to quantitative analytic modeling within the Synchrony Model Governance and Validation team. Your passion for model validation and modeling techniques will be greatly valued in Synchrony's Risk team. Key Responsibilities: - Conduct full scope model review, annual review, and ongoing monitoring of model performance for both internally and vendor-developed models, particularly in the areas of loss forecast, with effective challenges to identify potential issues. - Evaluate model development data quality, methodology conceptual soundness, accuracy, and conduct model performance testing including back-testing, sensitivity analysis, benchmarking, etc. to timely identify and highlight issues. - Perform proper documentation within expected timeframes to effectively highlight findings for further review/investigation and facilitate informed discussions on key analytics. - Conduct in-depth analysis of large data sets, support the review and maintenance process of relevant models, and model validation documentation. - Communicate technical information verbally and in writing to both technical and business teams effect