Senior Associate, Quantitative Analysis - Commercial Finance

Senior Associate, Quantitative Analysis - Commercial Finance

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 contains an approximately $100B loan portfolio that has grown by virtue of several acquisitions. It is a Portfolio of Commercial & Industrial, Commercial Real Estate, and various specialty lending. Capital One's Commercial Bank also has over $30B of Commercial deposits. The Modeling Data & Analytics Team within Commercial Finance is responsible for the modeling work of forecasting the volume and net interest income of the Commercial Portfolio. 

Responsibilities and Skills:

• Partner with the various lines of business to develop and enhance Commercial Finance modeling and analytical framework, such as loan/deposit balance forecasting, loan/deposit spread models and revenue forecasting

• Work across Capital One entities to create novel analytical solutions to challenging business problems

• Identify opportunities to apply quantitative and analytical methods including time series modeling, statistical regression, machine learning algorithms, and simulations to generate critical insights and decision frameworks for our business and customers

• Identify opportunities to apply automation solutions to improve business performance and process efficiencies

• Collaborate in a cross-disciplinary team to build cloud-based solutions grounded in data

• Provide technical guidance to business leadership

• Communicate technical subject matter clearly and concisely to individuals from various backgrounds

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 will possess:

• Understanding of quantitative modeling in relation to Commercial loan portfolio and deposit behaviors

• Extensive experience in Python or other object-oriented language

• Ability to clearly communicate modeling results to a wide range of audiences

• Ability to collaborate effectively with cross-functional partners and contribute as a supportive team player

• Drive to develop and maintain high quality and transparent model documentation

• Strong written and verbal communication skills

• Strong presentation skills

• Ability to own the model development process from conceptualization through data exploration, model selection, validation, deployment, business user training, and monitoring

• Deep knowledge of Commercial products, financial statements and balance sheet management

Basic Qualifications:

• 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 3 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 1 year of experience performing data analytics

Preferred Qualifications:

• Master’s Degree in Statistics, Economics, Mathematics, Financial Engineering, Operations Research, Engineering, Finance, Physics or related discipline

• 2 years of experience with data analysis