Manager, Quantitative Analysis - Model Risk Audit
About The Position
At Capital One, data is central to 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, which was cutting-edge technology in 1988. Fast-forward a few years, and this innovation and our passion for data have propelled us to a Fortune 200 company and a leader in data-driven decision-making. As a Quantitative Analyst at Capital One, you will be part of a team leading the next wave of disruption at a large scale, utilizing the latest in cloud computing and machine learning technologies and operating across billions of customer records to unlock opportunities that help people save money, time, and reduce financial stress. As part of Capital One’s Model Audit team, you will have a unique perspective to review models and model risk practices across the enterprise and the opportunity to identify and raise model risk issues, providing assurance to the Audit Committee. Successful candidates will collaborate cross-functionally with business units throughout the company to deliver breakthrough analytical solutions supporting a winning strategy in a constantly evolving business environment.
Requirements
- 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.
- Proficiency in key econometric and statistical techniques (predictive modeling, logistic regression, survival analysis, panel data models, design of experiments, decision trees, machine learning methods).
- Desire to remain on the leading edge of analytical technology with a passion for the newest and most innovative tools.
- Currently have, or are in the process of obtaining one of the following with an exception that the required degree will be obtained on or before the scheduled start date: A 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.
- A 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 audience.
- 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).
Nice To Haves
- 5 years of experience with Python, R or other statistical analyst software.
- 5 years of experience in statistical modeling or regression analytics or machine learning.
- At least 2 years of experience in derivative modeling (Fixed income, Commodity, FX or CDS).
Responsibilities
- Apply deep expertise in econometric, statistical, and machine learning methods to generate critical insights and decision frameworks for our business and customers.
- Remain on the leading edge of analytical technology with a passion for the newest and most innovative tools.
- Communicate technical subject matter clearly and concisely to individuals from various backgrounds.
- Partner with various lines of business to enhance modeling and analytical frameworks.
- Work across Capital One entities to create novel analytical solutions to challenging business problems.
- Identify opportunities to apply quantitative methods, machine learning, and automation solutions to improve business performance and process efficiencies.
- Collaborate in a cross-disciplinary team to build cloud-based solutions grounded in data.
- Develop and maintain high-quality and transparent documentation.
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).
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What This Job Offers
Job Type
Full-time
Career Level
Manager
