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Led a pod of quantitative analysts to develop simulation-based structural models to project credit risk losses for the Structured Finance LOB, covering a wide range of applications, e.g. internal risk rating, loss forecasting, stress testing, and loan pricing
Partner with the Business Analyst, Underwriter, Credit Officer and other key stakeholders to understand the deal structure, cash flow dynamics, key risk drivers and translate them into actionable items to generate business insights, enhance and consolidate existing model structures, and drive for meaningful changes
Collaborate with implementation and data infrastructure team to build cloud-based solutions for model deployment, monitoring, and maintenance
Work effectively with challenge functions to ensure prompt and comprehensive support for model validation and model governance
Communicate technical subject matter clearly and concisely to various model stakeholders through verbal and written communication; Prepare presentations of complex technical concepts and research results to non-specialist audiences and senior management with strong storytelling skills
Draft and maintain high quality and transparent model documentation
Remain on the leading edge of analytical technology with a passion for the newest and most innovative tools; Leverage the latest open source technologies and enterprise-level tools to proactively identify areas of opportunities in our existing framework and processes
Successful candidates will possess:
Strong ability to grasp and internalize the economics and risk drivers behind complex Structured lending products within the Commercial Bank for modeling purposes
Excellent coding skills in Python (must-have) and/or R (good to have) with self-drive to lead the team to create and review codes with industry best practices
Excellent communication and storytelling skills to synthesize data and modeling insights and present to key model stakeholder and senior management
Hands-on experience with data analysis to gain insights from large datasets and create interactive dashboards
Experience with a variety of modeling techniques, e.g. structural model, simulation-based model, statistical and/or machine learning model
Drive to continuously improve all aspects of their work in a collaborative fashion
Basic Qualifications:
Currently has, or is in the process of obtainingone of the followingwith an expectation that the required degree will be obtained on or before the scheduled start date:
A Bachelor's Degree in a quantitative field (Statistics, Economics, Operations Research, Analytics, Mathematics, Computer Science, or a related quantitative field) plus 6 years of experience performing data analytics
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 performing data 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 performing data analytics
Preferred Qualifications:
PhD in Statistics, Economics, Mathematics, Financial Engineering, Operations Research, Engineering, Finance, Physics or related disciplines
4 years of experience in statistical modeling, regression analytics or machine learning
2 years of experience with Python, R or other statistical analyst software
. Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level.
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 . All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations.
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