Principal Quantitative Analyst - Model Risk

Capital One
McLean, Virginia
Jan 14, 2021
Feb 12, 2021
Full Time
McLean 1 (19050), United States of America, McLean, Virginia

Principal Quantitative Analyst - Model Risk

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 a Principal Quantitative Analyst within the Model Risk Office, you will validate financial forecasting and stress testing models used to measure risk and calculate capital requirements. You will initially focus on finance forecasting models but over time will gain exposure to diverse modeling techniques, including time series, logistic regression and machine learning. In addition you will get exposures to various asset classes including credit cards, auto loans, and investment securities. Validations cover all aspects of model development and performance and include forward-looking advancements in model sophistication and quality. You will enhance your technical and analytical skills, while also working with business leaders to understand and influence business strategies. With a network of over 200 quantitative analysts, data scientists and statisticians, we've created a dynamic environment with ample opportunities for learning and growth.

Responsibilities and Skills:

- Develop and implement validation strategies for statistical, financial, and other quantitative models used in revenue forecasting, stress, and capital calculations

- Assess the quality and risk of model methodologies, outputs, and processes

- Partner with the various lines of business to enhance modeling and analytical framework.

- Apply deep expertise in econometric, statistical and machine learning methods to generate critical insights in assessing model risks and opportunities.
- Communicate clearly and concisely both verbally and through written communication via model validation reports and presentations

- Identify opportunities to apply quantitative methods and automation solutions to improve business performance and process efficiencies.

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

- 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)

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 2 years of experience in data analytics or financial modeling or econometric modeling (can include Graduate School Research work).

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.

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

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