Principal Associate - Quantitative Analyst - Credit Risk Loss Forecasting

Employer
Capital One
Location
New York, New York
Posted
Sep 25, 2022
Closes
Oct 24, 2022
Ref
R151227
Function
Finance
Hours
Full Time
NYC 299 Park Avenue (22957), United States of America, New York, New York

Principal Associate - Quantitative Analyst - Credit Risk Loss Forecasting

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 in Capital One's Commercial Bank, you'll be part of a team using modern technology to disrupt, generate insights, and drive critical business planning. The Commercial Bank has a $100B+ loan portfolio that has grown organically and via acquisitions, covering Commercial and Industrial, Commercial Real Estate, and Structured Products.

On this team, you'll get an opportunity to develop credit loss models, decomposed into dual risk ratings for probability and severity of loss, for a diverse set of portfolios with a diverse set of tools and challenges. This will involve blending business thinking and economic fundamentals with quantitative tools to forecast rare credit default and loss events. It's a growing team, full of exciting opportunities to solve complex problems across a range of portfolios.

Responsibilities and Skills:
  • Lead a team of quantitative analysts to develop deep modeling expertise, business context, and relationships in a business vertical, e.g., Commercial & Industrial lending, or Structured Products lending
  • Create credit risk rating models that are robust, intuitive, well-grounded, and that support Commercial business and credit experts in their decision making.
  • Collaborate with other credit modeling functions (e.g., ACL, CCAR) to ensure a coherent and cohesive suite of models to forecast losses for the entire Commercial Bank.
  • Work effectively with challenge functions to ensure prompt and comprehensive support.
  • Maintain the existing suite of models and tools for accuracy, compliance, and user support.
  • Understand technical issues in econometric and statistical modeling and apply these skills toward developing models and assessing model risks and opportunities.
  • Effectively communicate technical subject matter to individuals from various backgrounds both verbally and through written materials.
  • 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 statistical-learning and econometric analysis.
  • Desire to remain on the leading edge of analytical technology with a passion for the newest and most innovative tools.
  • Strong coding skills in R or Python and drive to create efficient, accurate, and maintainable code with best practices
  • Ability to clearly communicate modeling results to a wide range of audiences.
  • Drive to develop and maintain high quality and transparent model documentation.
  • Reverence for processes, controls, governance, and building good infrastructure
  • Ability to manage a small team and complex projects that require cross-team collaboration


Basic Qualifications:
  • Bachelor's Degree plus at least 5 years of experience in data analytics, or Master's Degree plus at least 3 years of experience in data analytics (can include Graduate School Research work) or PhD.
  • At least 2 years of programming experience.


Preferred Qualifications:
  • PhD in Statistics, Economics, Mathematics, Financial Engineering, Operations Research, Engineering, Finance, Physics or related disciplines.
  • 5 years of experience in statistical modeling or regression analytics or machine learning.
  • 4-6 years of credit risk modeling experience for commercial bank, such as default probability, loss given default, exposure at default etc.
  • 2 years of experience managing a team of analysts


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

No agencies please. 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, race, color, age, national origin, religion, physical and mental disability, genetic information, marital status, sexual orientation, gender identity/assignment, citizenship, pregnancy or maternity, protected veteran status, or any other status prohibited by applicable national, federal, state or local law. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections 4901-4920; New York City's Fair Chance Act; Philadelphia's Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries.

If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1-800-304-9102 or via email at RecruitingAccommodation@capitalone.com . All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations.

For technical support or questions about Capital One's recruiting process, please send an email to Careers@capitalone.com

Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site.

Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).

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