Quant Va Jobs (NOW HIRING)

Location: Richmond, VA

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 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 big opportunities that help everyday people save money, time and agony in their financial lives.

Capital One’s Commercial Bank Team has a $100B+ loan portfolio covering C&I, CRE, and structured products. On this team you’ll 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 outcomes across multi‑million record datasets; in others you’ll use different skill sets, blending business thinking with quantitative tools when forecasting rare or unprecedented events.

• Develop Commercial Real Estate credit risk models for internal risk rating, loss forecasting, stress testing, and pricing.
• Partner with the business analyst team to enhance modeling and analytical frameworks, generating business insights and driving change.
• Proactively identify opportunities to apply quantitative methods and automation solutions to improve model performance and process efficiencies.
• Collaborate with implementation and data infrastructure teams 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.

Expertise in quantitative analysis is central to our success in all markets. Our modelers thrive in a culture of mutual respect, excellence, and innovation.

• Excellent coding skills in Python or R with the ability to create accurate, efficient, and organized code using best practices.
• Hands‑on experience with data analysis and visualization packages to gain insights from large datasets.
• Deep understanding of quantitative analysis methods with practical considerations in financial institutions and/or commercial bank lending.
• Demonstrated track record in applying statistical, machine learning or econometric analysis to solve business problems.
• Drive to develop and maintain high‑quality and transparent model documentation.
• Strong written and verbal communication skills and storytelling ability for presentations.
• Appreciation for processes, controls, and good governance.

• Currently has or is in the process of obtaining one of the following with an expectation that the degree will be obtained on or before the scheduled start date:
  • Bachelor’s Degree in a quantitative field plus 3 years of experience performing data analytics.
  • Master’s Degree in a quantitative field or an MBA with a quantitative concentration plus 1 year of experience performing data analytics.

• Master’s Degree or PhD in Statistics, Economics, Mathematics, Financial Engineering, Operations Research, Engineering, Finance, Physics or related discipline.
• At least 2 years of experience with data analysis.
• At least 1 year of experience with Python, R or other statistical analysis software.

Capital One will consider sponsoring a new qualified applicant for employment authorization for this position.

• Richmond, VA: $120,900 – $138,000
• McLean, VA: $133,000 – $151,800

This role is eligible for performance‑based incentive compensation, including cash bonuses and/or long‑term incentives. Capital One offers a comprehensive, competitive, and inclusive set of health, financial, and other benefits that support your total well‑being.

Capital One is an equal opportunity employer committed to diversity and inclusion in the workplace. All qualified applicants will receive consideration for employment without regard to sex, age, race, color, national origin, religion, disability, genetic information, marital status, sexual orientation, gender identity, citizenship, or any other protected class.