Senior Associate, Quantitative Analyst - Model Risk Office
As part of the Model Risk function, you will partner with high-performing model development teams and model risk teams responsible for advance Capital One’s Loan Loss Forecasting and Allowance for Credit Losses (ACL) framework.
Responsibilities and Skills:
- Partner with the various lines of business to enhance modeling and analytical framework.
- Work across Capital One entities to create novel analytical solutions to the challenging business problems.
- Identify opportunities to apply quantitative methods and automation solutions to improve business performance and process efficiencies.
- Collaborate in a cross-disciplinary team to build cloud-based solutions grounded in data.
- Identify opportunities to apply quantitative methods or machine learning to improve business performance.
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 machine learning and econometric analysis.
- Experience utilizing model estimation tools.
- Ability to clearly communicate modeling or validation results to a wide range of audiences.
- Drive to develop and maintain high quality and transparent model documentation or validation reports.
- Strong written and verbal communication skills.
- Strong presentation skills.
Basic Qualifications:
Currently has, or is 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 1 year of experience in quantitative analytics
At least 1 year 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 1 year 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:
Capital One will consider sponsoring a new qualified applicant for employment authorization for this position.
The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked.
McLean, VA: $135,600 - $154,800 for Sr Assoc,Quantitative AnalysisAnytown, IL: $123,300 - $140,700 for Sr Assoc,Quantitative Analysis
Riverwoods, IL: $123,300 - $140,700 for Sr Assoc,Quantitative Analysis
Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate’s offer letter.
This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan.
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.
This role is expected to accept applications for a minimum of 5 business days.
