Manager, Quantitative Analysis

About the Role

Capital One is seeking a Manager for a Model Validation team within the Model Risk Office. This role involves working closely with business groups to ensure the accuracy and robustness of the firm’s market risk models. Clients of the group include senior management, business leads, internal audit, and regulators.

Key Responsibilities

• Develop model approaches to assess model design and advance future capabilities.
• Understand relevant business processes and portfolios associated with model use.
• Understand technical issues in econometric, statistical, and machine learning modeling, and apply these skills toward developing models and assessing model risks and opportunities.
• Communicate technical subject matter clearly and concisely to individuals from various backgrounds, both verbally and through written communication.
• Prepare presentations of complex technical concepts and research results to non-specialist audiences and senior management.
• Maintain the efficiency and accuracy of models through continuous improvement and application of best practices.
• Develop and maintain high-quality and transparent documentation.
• Leverage the latest open-source technologies and tools to identify areas of opportunity in the existing framework.
• Remain on the leading edge of analytical technology with a passion for the newest and most innovative tools.

Key Responsibilities (Specific)

• Responsible for validating models, specifically those used for derivative pricing and risk management, including derivative valuation, market risk, and counterparty risk models.

Requirements & Tech Stack

• Python or R
• Open-source technologies and tools
• Agile development methodologies

Qualifications

• Demonstrated track record in modeling and experience utilizing model estimation tools.
• Ability to clearly communicate modeling results to management, model risk office, regulators, and other modelers.
• Drive to continuously improve all aspects of their work in a collaborative fashion.
• Experience in machine learning.
• Strong communication skills with the ability to quickly understand existing models and new requirements/business needs.
• Strong grasp of econometric theory and methodologies.
• Desire to remain on the leading edge of analytical technology with a passion for the newest and most innovative tools.
• Experience working with CCAR regulatory requirements.
• Experience with derivative modeling.

Basic Qualifications

• 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, plus 4 years of experience in quantitative analytics.
• PhD in a quantitative field (Statistics, Economics, Operations Research, Analytics, Mathematics, Computer Science, or a related quantitative field), plus 1 year of experience in quantitative analytics.
• At least 4 years of experience in each of the following skills through education or experience:
• Statistical or econometric modeling
• Linear and logistic regression
• Programming in R, Python, or SQL
• Presenting statistical concepts and research results to non-statistical audiences.
• At least 4 years of experience in at least 3 of the following skills:
• 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)

Preferred Qualifications

• 5 years of experience with Python, R, or other statistical analyst software.
• 5 years of experience in statistical modeling, regression analytics, or machine learning.
• At least 2 years of experience in derivative modeling (Fixed income, Commodity, FX or CDS).