Locations: VA - McLean, United States of America, McLean, Virginia

Manager - Quantitative Analysis

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.

In this role with our Counterparty Credit Risk Group, you will be at the forefront of assessing and mitigating potential credit and market risks associated with our counterparties in financial transactions. As you build data pipelines, critical reports, and cutting-edge credit and exposure models, you will play an integral role in safeguarding our financial future while thriving in a fast-paced and intellectually stimulating environment.

Responsibilities and Skills:

• Manage and contribute to firm-wide projects around key counterparty credit exposure metrics and technical enhancements
  
• Collaborate in a cross-disciplinary team to build cloud-based, real-time, intelligent solutions grounded in data, including data pipelines, reports, and custom queries
  
• Partner with internal teams to enhance statistical modeling and analytical framework for counterparty credit risk ranking and exposure measurement
  
• Solve analytical problems and effectively communicate methodologies and results
  
• Identify opportunities to apply quantitative methods, machine learning and automation solutions to improve business performance and process efficiencies
  
• Develop and manage documentation for counterparty exposure calculations, data flows, and technical processes
  

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 data analytics, machine learning or econometric analysis
  
• Strong coding skills in modern scripting languages such as Python or R
  
• Ability to clearly communicate complex statistical concepts and research results to non-statistical audience
  
• Strong written and verbal communication skills and ability to document analyses for reproducibility
  

Basic Qualifications:

• Bachelor's Degree plus at least 6 years of experience in data analytics, or Master's Degree plus at least 4 years of experience in data analytics, or PhD plus at least 1 year of experience in data analytics, financial modeling or econometric modeling (can include Graduate School Research work)
  

Preferred Qualifications:

• At least 3 years of experience with professional credit risk or market risk responsibility
  
• At least 2 years of experience programming with tabular data (preferably in Python, acceptably in R)
  
• Master's Degree in a highly quantitative field (Statistics, Economics, Mathematics, Financial Engineering, Operations Research, Computer Science/Machine Learning or Technology related discipline)
  
• At least 3 years of experience developing and managing data pipelines, including experience working with large-scale, cloud-based coding environments and databases
  
• Experience with developing and maintaining custom reports and queries in Business Intelligence Software, such as Tableau or Amazon Web Services' Quicksight
  
• Experience with developing and implementing models using modern scripting languages (Python, R or other statistical languages) and working with data using query languages such as SQL
  
• Experience in statistical techniques such as classification, clustering, regression, and natural language processing
  
• Professional certifications, such as FRM (Financial Risk Manager) or CFA (Chartered Financial Analyst)
  

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

Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website . Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level.

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).