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About the Role

Capital One's Counterparty Risk Group manages a significant credit risk portfolio for Financial Institutions, Global Payment Networks, and the Commercial Bank. This role offers the opportunity to solve diverse problems using various tools, including open-source programming and cloud computing, to predict credit risk events and forecast rare events. The team generates critical insights for credit decision-makers.

Responsibilities

Communicate clearly and concisely both verbally and through written communication via model validation presentations and reports and presentations.
Develop and implement strategies for statistical and financial models used to support Counterparty Credit Risk processes.
Assess the quality and risk of model methodologies, outputs, and processes.
Develop alternative approaches to model design and deployment capabilities.
Apply expertise in econometric, statistical, and machine learning methods to generate insights in modeled risks.
Identify opportunities to apply quantitative methods and automation solutions to improve business performance and process efficiencies.

Requirements

Strong understanding of quantitative analysis methods relating to financial institutions and financial risk exposures.
Demonstrated track-record in model development and/or validation.
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.
Appreciation for processes, controls, and good governance.
Ability to manage complex projects that require cross-team collaboration.

Skills

Statistical or econometric modeling
Linear and logistic regression
Programming in R, Python, or SQL
Presenting statistical concepts and research results to non-statistical audience
Survival analysis modeling
Time-series analysis
Panel data (longitudinal data or cross-sectional time-series data) analysis
Cross-sectional data analysis
Machine learning
Analysis and management of large datasets (>1M records)
Python
Scala
R

Location

McLean, VA
New York, NY

Work Type

Full-time

Experience Level

Master's degree in a quantitative field or MBA with quantitative concentration plus 7 years of experience in quantitative analytics
PhD in a quantitative field plus 4 years of experience in quantitative analytics
At least 7 years of experience in statistical or econometric modeling, linear and logistic regression, programming in R, Python, or SQL, and presenting statistical concepts and research results to non-statistical audience
At least 7 years of experience in at least 3 of the following: Survival analysis modeling, Time-series analysis, Panel data analysis, Cross-sectional data analysis, Machine learning, Analysis and management of large datasets (>1M records)
8 years of experience in Python, Scala, R or other statistical analyst software
8 years of experience with machine learning
3 years of experience managing people

Education Level

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
PhD in a quantitative field (Statistics, Economics, Operations Research, Analytics, Mathematics, Computer Science, or a related quantitative field)

Salary/Compensations

McLean, VA: $269,100 - $307,200
New York, NY: $293,600 - $335,100

Benefits

Comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being.
Eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI).

About the Company

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.
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).

Equal Opportunity

Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws.
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.