Senior Associate, Quantitative Analyst - 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 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.

As part of the Model Risk function, you will partner with high-performing model development teams and model risk teams responsible for advance Capital One’s Loan Loss Forecasting and Allowance for Credit Losses (ACL) framework.

Responsibilities and Skills: - Partner with the various lines of business to enhance modeling and analytical framework. - Work across Capital One entities to create novel analytical solutions to the challenging business problems. - Identify opportunities to apply quantitative methods and automation solutions to improve business performance and process efficiencies. - Collaborate in a cross-disciplinary team to build cloud-based solutions grounded in data. - Identify opportunities to apply quantitative methods or machine learning to improve business performance.

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 in relation to financial institutions. - Demonstrated track-record in machine learning and econometric analysis. - Experience utilizing model estimation tools. - Ability to clearly communicate modeling or validation results to a wide range of audiences. - Drive to develop and maintain high quality and transparent model documentation or validation reports. - Strong written and verbal communication skills.

Strong presentation skills.