Senior Manager, Quantitative Analysis - Model Risk Office

Senior Manager, Quantitative Analysis – Model Risk Office At Capital One data is at the center of everything we do. As a startup, we disrupted the credit card industry by personally tailoring every credit card offer using statistical modeling and relational databases, cutting‑edge technology in 1988. That innovation and our passion for data has propelled us to a Fortune 200 company and a leader in data‑driven decision making. As the Quantitative Senior Manager, you will be part of a team leading the next wave of disruption at a whole new scale, using the latest cloud computing and machine learning technologies and operating across billions of customer records to unlock opportunities that help everyday people save money, time, and financial pain. In the Model Risk function, you will partner with high‑performing model development and model risk teams that advance Capital One’s Loan Loss Forecasting and Allowance for Credit Losses (ACL) framework. Responsibilities and Skills Remain at the leading edge of analytical technology with a passion for innovative tools. Develop alternative model approaches to assess model design and advance future capabilities. Understand relevant business processes and portfolios associated with model use. Address technical issues in econometric, statistical, and machine learning modeling and apply these skills to develop models and assess model risks and opportunities. Communicate technical subject matter clearly and concisely to individuals from varied backgrounds, both verbally and in written communication; prepare presentations of complex technical concepts for non‑specialist audiences and senior management. Maintain the efficiency and accuracy of models through continuous improvement and best‑practice application. Develop and maintain high‑quality, transparent documentation. Leverage open‑source technologies and tools to identify opportunities in the existing framework. Basic Qualifications Currently holds or is in the process of obtaining one of the following: A Master’s degree in a quantitative field (Statistics, Economics, Operations Research, Analytics, Mathematics, Computer Science, or a related quantitative field) or an MBA with a quantitative concentration plus 5 years of quantitative analytics experience. A PhD in a quantitative field (Statistics, Economics, Operations Research, Analytics, Mathematics, Computer Science, or a related quantitative field) plus 2 years of quantitative analytics experience. At least 5 years of experience in each of the following areas: Statistical or econometric modeling Linear and logistic regression Programming in R, Python, or SQL Presenting statistical concepts and research results to non‑statistical audiences At least 5 years of experience in at least 3 of the following areas: Survival analysis modeling Time‑series analysis Panel data (longitudinal or cross‑sectional time‑series) analysis Cross‑sectional data analysis Machine learning Analysis and management of large datasets (over 1 million records) Preferred Qualifications 6 years of experience with Python, R, or other statistical software. 6 years of experience in statistical modeling, regression analytics, or machine learning. 2 years of experience managing people. Additional Information Capital One will consider sponsoring a qualified applicant for employment authorization for this position. Competitive salary ranges vary by location. Example: McLean, VA – $229,900 to $262,400 for Sr Mgr, Quantitative Analysis. Bonus and incentive compensation may be available, and Capital One offers a comprehensive set of health, financial, and other benefits that support overall well‑being. Capital One is an equal‑opportunity employer, committed to non‑discrimination in compliance with applicable federal, state, and local laws. The company promotes a drug‑free workplace and will consider qualified applicants with a criminal history in a manner consistent with applicable laws. If you need reasonable accommodations, please contact Capital One Recruiting at View phone number on click.appcast.io or email View email address on click.appcast.io. All information you provide will remain confidential and will be used only as required to provide accommodations. For technical support or questions about Capital One’s recruiting process, please contact View email address on click.appcast.io. #J-18808-Ljbffr Hobbsnews