Manager, Quantitative Analysis - Commercial Credit Modeling Team

Capital One•McLean, VA

About The Position

Manager, Quantitative Analysis - Commercial Credit Modeling Team At Capital One data is at the center of 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, cutting edge technology in 1988! Fast-forward a few years, and this little innovation and our passion for data has skyrocketed us to a Fortune 200 company and a leader in the world of data-driven decision-making. As a Quantitative Analyst at Capital One, you’ll be part of a team that’s leading the next wave of disruption at a whole new scale, using the latest in cloud computing and machine learning technologies and operating across billions of customer records to unlock the big opportunities that help everyday people save money, time and agony in their financial lives. Capital One’s Commercial Bank has a $100B+ loan portfolio that has grown organically and via acquisitions, covering C&I, CRE, and Structured Products. On the Commercial Credit Modeling Team, 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 loss across multi-million record datasets using statistical techniques. In other settings, you’ll get the opportunity to use completely different skill sets, blending business thinking with simulation and 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. Expertise in quantitative analysis is central to our success in all markets. Our modelers thrive in a culture of mutual respect, excellence and innovation.

Requirements

Strong understanding of quantitative analysis methods in relation to corporate credit
Demonstrated track-record in applying statistical and econometric analysis in areas with low probability events
Intellectual curiosity, business intuition, and a drive to produce best estimates that balance confidence and uncertainty
Desire to remain on the leading edge of analytical technology with a passion for finding value in the newest and most innovative tools
Consulting experience in the financial sector
Excellent coding skills in Python (must-have) and/or R (good to have) with drive to create accurate, efficient, and organized code using industry best practices
Ability to clearly communicate modeling results and recommendations to senior leaders and maintain high standards of documentation
Reverence for processes, controls, governance, and infrastructure
Passion for collaboration, mentorship, and leading by example
Currently has, or is in the process of obtaining one of the following with an expectation that the required degree will be obtained on or before the scheduled start date: A Bachelor's Degree in a quantitative field (Statistics, Economics, Operations Research, Analytics, Mathematics, Computer Science, or a related quantitative field) plus 6 years of experience performing data analytics 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 4 years of experience performing data analytics A PHD in a quantitative field (Statistics, Economics, Operations Research, Analytics, Mathematics, Computer Science, or a related quantitative field) plus 1 year of experience performing data analytics

Nice To Haves

PhD in Statistics, Economics, Mathematics, Financial Engineering, Operations Research, Engineering, Finance, Physics or related disciplines.
5+ years of experience in statistical modeling, regression analytics or machine learning.
4+ years of credit risk modeling experience for commercial banks (default probability, loss given default, or exposure at default.)
2+ years of experience managing a team of analysts.

Responsibilities

Develop credit risk models for various business applications, including internal risk rating, loss forecasting, stress testing, profitability for Commercial and Industrial lending
Lead high impact, complex, model development projects end to end from ideation, to data processing, to methodology and model selection, to socialization and implementation
Partner with the business analyst team to enhance modeling and analytical frameworks to generate business insights, identify and mitigate model weaknesses, and drive changes
Proactively identify opportunities to apply quantitative methods and automation solutions to improve model performance and process efficiencies
Collaborate with implementation and data infrastructure team to build cloud-based solutions for model deployment, monitoring, and maintenance
Work effectively with challenge functions to ensure prompt and comprehensive support for model governance

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