Director, Quantitative Analysis - Commercial Credit Modeling Team
Capital One’s Counterparty Risk Group has a $7B+ credit risk portfolio toward Financial Institutions across the Enterprise. We also extend credit risk management to the Global Payment Network and the Commercial Bank at the intersection of financial institutions and commercial lending. In the Counterparty Risk Group, you’ll get an opportunity to solve a diverse set of problems with a diverse set of tools. In some settings, you’ll leverage open source programming or cloud computing to predict credit risk events across complex datasets using statistical techniques. In other settings, you’ll get the opportunity to use completely different skill sets, blending business insights with quantitative tools when forecasting rare or unprecedented events. It’s a team full of exciting opportunities to solve a range of complex problems, generating insights for credit decision makers.
Responsibilities and Skills:
Communicate clearly and concisely both verbally and through written communication via model validation presentations and reports and presentations.
Develop and implement strategies for statistical and financial models used to support Counterparty Credit Risk processes.
Assess the quality and risk of model methodologies, outputs, and processes.
Develop alternative approaches to model design and deployment capabilities.
Apply expertise in econometric, statistical, and machine learning methods to generate insights in modeled risks.
Identify opportunities to apply quantitative methods and automation solutions to improve business performance and process efficiencies.
Expertise in quantitative analysis is central to our success in all markets. Our modelers thrive in a culture of mutual respect, excellence and innovation.
Successful candidates would possess:
Strong understanding of quantitative analysis methods relating to financial institutions and financial risk exposures.
Demonstrated track-record in model development and/or validation.
Ability to clearly communicate modeling results to a wide range of audiences.
Drive to develop and maintain high quality and transparent model documentation.
Strong written and verbal communication skills.
Strong presentation skills.
Appreciation for processes, controls, and good governance.
Ability to manage complex projects that require cross-team collaboration.
Basic Qualifications:
Preferred Qualifications:
8 years of experience in Python, Scala, R or other statistical analyst software
8 years of experience with machine learning
3 years of experience managing people
Capital One will consider sponsoring a new qualified applicant for employment authorization for this position.
The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked.
McLean, VA: $269,100 - $307,200 for Director, Quantitative Analysis
New York, NY: $293,600 - $335,100 for Director, Quantitative Analysis
Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate’s offer letter.
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.
Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website. Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level.
This role is expected to accept applications for a minimum of 5 business days.