Capital One

Position Title/Short Description

Full Text of JOE Listing:

Capital One is one of the world’s largest, most analytically sophisticated financial service providers. Our growing Fortune 100 company is known for giving affordable access to credit to tens of millions of customers worldwide. We also provide auto and business loans, plus banking and other financial services.

Expertise in quantitative analysis is central to our success in all these markets. Our 100+ modelers thrive in a culture of mutual respect, excellence and innovation. We have several opportunities available for top-notch quantitative professionals.

This position is part of Capital One’s Credit Risk Management Modeling team that uses multiple cloud-based open-sourced technologies to develop econometric and machine learning models and analytics to predict and generate insight into Capital One’s risk and capital needs. We blend cutting-edge quantitative methods with deep understanding of our business, data, and regulatory environment to build predictive models for credit and operational losses, volumes and outstanding balances in support of loss forecasting, CECL/allowance, stress testing, and capital allocation for Capital One. Our models and analyses inform earnings call prep, vertical resilience and downturn preparedness initiatives.

In this position, you’ll be part of a team tasked with ushering in the next wave of disruption to predictive modeling - using the latest in technology to build & deploy models and solutions leveraging new data sources to provide powerful new insights about our portfolio resilience and opportunities

Responsibilities and Skills:
- Partner with various lines of business to enhance modeling and analytical framework.
- Work across Capital One entities to create novel analytical solutions to 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.
- Apply deep expertise in econometric, statistical and machine learning methods to generate critical insights and decision frameworks for our business and customers.
- Provide technical guidance to business leadership.
- Communicate technical subject matter clearly and concisely to individuals from various backgrounds.

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

Basic Qualifications:
- Bachelor’s Degree plus 4 years of experience in Quantitative Analytics or Data Analytics, or Master’s degree plus 1 year of experience in Quantitative Analytics or Data Analytics, or PhD in a Quantitative Analytics or Data Analytics.
- At least 1 years of experience in data analytics or financial modeling or econometric modeling (can include Graduate School Research work).
- At least 2 years of programming experience.

Preferred Qualifications:
- Master’s Degree or PhD in Statistics, Economics, Mathematics, Financial Engineering, Operations Research, Engineering, Finance, Physics or related discipline.
- 1 year of experience with Python, R or other statistical analyst software
- 2 years of experience with data analysis
- 1 year of experience manipulating and analyzing large data sets.
- Proficiency in key econometric and statistical techniques (such as predictive modeling, logistic regression, survival analysis, panel data models, design of experiments, decision trees, machine learning methods)

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