Senior Manager, Quantitative Analysis - Model Risk Office

Capital One • McLean, VA

1d • $229,900 - $262,400 • Onsite

About The Position

At Capital One, data is central to everything we do. As a startup, we disrupted the credit card industry by individually personalizing every credit card offer using statistical modeling and the relational database, which was cutting-edge technology in 1988. Fast-forward a few years, and this innovation and our passion for data have propelled us to a Fortune 200 company and a leader in data-driven decision-making. As a Quantitative Senior Manager at Capital One, you will be part of a team leading the next wave of disruption at a large scale, utilizing the latest cloud computing and machine learning technologies and operating across billions of customer records to unlock significant opportunities that help people save money, time, and reduce financial stress. Within the Model Risk function, you will collaborate with high-performing model development teams and model risk teams responsible for advancing Capital One’s Loan Loss Forecasting and Allowance for Credit Losses (ACL) framework. You will provide effective challenge on quantitative models, evaluating their conceptual and statistical soundness, performance under economic stress scenarios, and alignment with model policy. The ideal candidate possesses deep retail credit risk expertise, strong regulatory knowledge, and a proven track record of driving rigorous model challenge.

Requirements

• Demonstrated track-record in modeling and experience utilizing model estimation tools such as Python or R.
• Ability to clearly communicate modeling results to management, model risk office, regulator and other modelers.
• Drive to continuously improve all aspects of their work in a collaborative fashion.
• Experience in machine learning.
• Strong communication skills with the ability to quickly understand existing models and new requirements/business needs.
• Experience working with Agile development methodologies.
• Strong grasp of econometric theory and methodologies.
• Desire to remain on the leading edge of analytical technology with a passion for the newest and most innovative tools.
• 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 experience in quantitative analytics OR A PhD in a quantitative field (Statistics, Economics, Operations Research, Analytics, Mathematics, Computer Science, or a related quantitative field) plus 2 years of experience in quantitative analytics
• At least 5 years of experience in each of the following skills through education or experience: Statistical or econometric modeling, Linear and logistic regression, Programming in R, Python, or SQL, Presenting statistical concepts and research results to non-statistical audience
• At least 5 years of experience in at least 3 of the following skills: Survival analysis modeling, Time-series analysis, Panel data (longitudinal data or cross-sectional time-series data) analysis, Cross-sectional data analysis, Machine learning, Analysis and management of large datasets (>1M records)

Nice To Haves

• 6 years of experience with Python, R or other statistical analyst software
• 6 years of experience in statistical modeling or regression analytics or machine learning
• 2 years of experience managing people

Responsibilities

• Remain on the leading edge of analytical technology with a passion for the newest and most innovative tools.
• Develop alternative model approaches to assess model design and advance future capabilities.
• Understand relevant business processes and portfolios associated with model use.
• Understand technical issues in econometric, statistical, and machine learning modeling and apply these skills toward developing models and assessing model risks and opportunities.
• Communicate technical subject matter clearly and concisely to individuals from various backgrounds both verbally and through written communication; prepare presentations of complex technical concepts and research results to non-specialist audiences and senior management.
• Maintain the efficiency and accuracy of our models through continuous improvement and application of best practices.
• Develop and maintain high quality and transparent documentation.
• Leverage the latest open source technologies and tools to identify areas of opportunity in our existing framework.

Benefits

• Comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being.
• Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level.
• This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan.

What This Job Offers

• Job Type: Full-time
• Career Level: Senior